Triple
T7559673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angel |
E178761
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Angelus |
E237394
|
NE FINISHED |
How this triple was built (2 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: Angelus | Statement: [Angel, hasVariant, Angelus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angelus Context triple: [Angel, hasVariant, Angelus]
-
A.
Angelus
chosen
The Angelus is a traditional Catholic prayer recited three times daily in honor of the Incarnation, often accompanied by the ringing of church bells.
-
B.
Angel of Death
Angel of Death is a thriller novel by Jack Higgins that follows covert operatives confronting a deadly terrorist organization in modern-day Britain.
-
C.
Archangel
Archangel is a historic Russian port city on the White Sea that served as a major northern gateway for European trade before the rise of St. Petersburg.
-
D.
Archangel
Archangel is a historical fiction collection by Andrea Barrett that intertwines science, war, and personal relationships in early 20th-century settings.
-
E.
Evil Angel
Evil Angel is a prominent American adult film production company known for its influential directors and high-quality, hardcore content.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8dd96488190b4cca25ae8f7f95c |
completed | March 27, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856cc869081909555ae03dec52288 |
completed | March 28, 2026, 10:31 p.m. |
Created at: March 27, 2026, 3:50 p.m.