Triple
T9501069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregorio |
E229139
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Grégoire (French) |
E251632
|
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: Grégoire (French) | Statement: [Gregorio, hasCognate, Grégoire (French)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grégoire (French) Context triple: [Gregorio, hasCognate, Grégoire (French)]
-
A.
David (French)
David (French) is the French form of the given name "David," commonly used in French-speaking countries and derived from the Hebrew name meaning "beloved."
-
B.
Grégoire
chosen
Grégoire is the French form of the given name Gregory, commonly used in French-speaking countries.
-
C.
Alain (French)
Alain is the French given name equivalent to the English name Alan, commonly used for males in French-speaking countries.
-
D.
Jean (French)
Jean is the standard French given name equivalent to the English name John, widely used for men in French-speaking countries.
-
E.
Morisyen
Morisyen is the French-based Creole language widely spoken in Mauritius and used as a key marker of the island’s national identity.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983d4b708190a4dfef1246986a26 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a0a5ec881908bb1643d2bea2c9f |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:57 p.m.