Triple
T16834595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salvete Virgines |
E409239
|
entity |
| Predicate | associatedWithFranchise |
P7425
|
FINISHED |
| Object |
The Da Vinci Code franchise
The Da Vinci Code franchise is a multimedia series originating from Dan Brown’s bestselling mystery-thriller novel, encompassing books and film adaptations centered on symbologist Robert Langdon and conspiracies involving religious history and secret societies.
|
E13796
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: The Da Vinci Code franchise | Statement: [Salvete Virgines, associatedWithFranchise, The Da Vinci Code franchise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Da Vinci Code franchise Context triple: [Salvete Virgines, associatedWithFranchise, The Da Vinci Code franchise]
-
A.
Robert Langdon film series
The Robert Langdon film series is a collection of mystery-thriller movies based on Dan Brown’s novels, following symbologist Robert Langdon as he unravels historical and religious conspiracies.
-
B.
The Da Vinci Code
The Da Vinci Code is a 2006 mystery thriller film based on Dan Brown’s bestselling novel, following symbologist Robert Langdon as he uncovers a conspiracy involving secret societies and religious history.
-
C.
Angels & Demons
Angels & Demons is a 2009 mystery-thriller film based on Dan Brown’s novel, following symbologist Robert Langdon as he races to stop a deadly conspiracy within the Vatican.
-
D.
The Lost Symbol (TV series)
The Lost Symbol is a television thriller series based on Dan Brown's novel, following symbologist Robert Langdon as he unravels a Masonic conspiracy in Washington, D.C.
-
E.
Priory of Sion
The Priory of Sion is a fictional secret society popularized by Dan Brown’s novel "The Da Vinci Code," where it is portrayed as an ancient brotherhood guarding hidden religious truths.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Da Vinci Code franchise Triple: [Salvete Virgines, associatedWithFranchise, The Da Vinci Code franchise]
Generated description
The Da Vinci Code franchise is a multimedia series originating from Dan Brown’s bestselling mystery-thriller novel, encompassing books and film adaptations centered on symbologist Robert Langdon and conspiracies involving religious history and secret societies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Da Vinci Code franchise Target entity description: The Da Vinci Code franchise is a multimedia series originating from Dan Brown’s bestselling mystery-thriller novel, encompassing books and film adaptations centered on symbologist Robert Langdon and conspiracies involving religious history and secret societies.
-
A.
Robert Langdon film series
The Robert Langdon film series is a collection of mystery-thriller movies based on Dan Brown’s novels, following symbologist Robert Langdon as he unravels historical and religious conspiracies.
-
B.
The Da Vinci Code
chosen
The Da Vinci Code is a 2006 mystery thriller film based on Dan Brown’s bestselling novel, following symbologist Robert Langdon as he uncovers a conspiracy involving secret societies and religious history.
-
C.
Angels & Demons
Angels & Demons is a 2009 mystery-thriller film based on Dan Brown’s novel, following symbologist Robert Langdon as he races to stop a deadly conspiracy within the Vatican.
-
D.
The Lost Symbol (TV series)
The Lost Symbol is a television thriller series based on Dan Brown's novel, following symbologist Robert Langdon as he unravels a Masonic conspiracy in Washington, D.C.
-
E.
Priory of Sion
The Priory of Sion is a fictional secret society popularized by Dan Brown’s novel "The Da Vinci Code," where it is portrayed as an ancient brotherhood guarding hidden religious truths.
- F. None of above.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31aa44c8190b4f402f1898e6998 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d452505c8190b6d37b54b2f665f0 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d4f1bfa48190903bedc43ed6db75 |
completed | May 10, 2026, 6:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d59b96108190a0e55f01529a0b64 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:23 a.m.