Triple
T12436161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martine Aubry |
E297148
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Martine |
E260455
|
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: Martine | Statement: [Martine Aubry, givenName, Martine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martine Context triple: [Martine Aubry, givenName, Martine]
-
A.
Martine
chosen
Martine is a feminine given name commonly used in French- and English-speaking countries.
-
B.
Chantal
Chantal is a commune located in the Sud Department of Haiti.
-
C.
Arlette
Arlette, also known as Herleva of Falaise, was the mother of William the Conqueror and a key figure in the early life of the first Norman king of England.
-
D.
Micheline
Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
-
E.
Marcelle
Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d8c8fd481909b35ac504127a1b6 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea44a808190af2c5a6633120814 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.