Triple
T19721647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gospel of Mary |
E473623
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Andrew
Andrew is a disciple figure who appears in early Christian writings, including non-canonical texts like the Gospel of Mary, where he participates in theological discussions and disputes.
|
E1391833
|
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: Andrew | Statement: [Gospel of Mary, featuresCharacter, Andrew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Context triple: [Gospel of Mary, featuresCharacter, Andrew]
-
A.
Andrew
Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
-
B.
Andrew
Andrew is a central character portrayed as an exceptionally devoted and loving father in the film "World's Greatest Dad."
-
C.
Andrew
Andrew is a subway station in South Boston on the Massachusetts Bay Transportation Authority's Red Line.
-
D.
Andrew
Andrew is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s broadcast news staff.
-
E.
Alan
Alan is a masculine given name of Celtic origin that has been widely used in English-speaking countries.
- 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: Andrew Triple: [Gospel of Mary, featuresCharacter, Andrew]
Generated description
Andrew is a disciple figure who appears in early Christian writings, including non-canonical texts like the Gospel of Mary, where he participates in theological discussions and disputes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Target entity description: Andrew is a disciple figure who appears in early Christian writings, including non-canonical texts like the Gospel of Mary, where he participates in theological discussions and disputes.
-
A.
Andrew
Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
-
B.
Andrew
Andrew is a subway station in South Boston on the Massachusetts Bay Transportation Authority's Red Line.
-
C.
Andrew
Andrew is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s broadcast news staff.
-
D.
Andrew
Andrew is a central character portrayed as an exceptionally devoted and loving father in the film "World's Greatest Dad."
-
E.
Alan
Alan is a masculine given name of Celtic origin that has been widely used in English-speaking countries.
- F. None of above. chosen
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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f483c481908c6b3114bf9c5934 |
completed | April 20, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07aba719b48190a8ce14facba8f7d6 |
completed | May 15, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_6a07adc08ca081908df09c099cb710c2 |
completed | May 15, 2026, 11:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ae4ba5a88190a6ab297fb99cdd9d |
completed | May 15, 2026, 11:37 p.m. |
Created at: April 10, 2026, 1:46 p.m.