Triple
T1282506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clémentine |
E27357
|
entity |
| Predicate | hasMasculineForm |
P15475
|
FINISHED |
| Object | Clément |
E142943
|
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: Clément | Statement: [Clémentine, hasMasculineForm, Clément]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clément Context triple: [Clémentine, hasMasculineForm, Clément]
-
A.
Clément
chosen
Clément is a French given name, equivalent to Clement in English, commonly used for males.
-
B.
Jérôme
Jérôme is a masculine given name of French origin, famously borne by Jérôme Bonaparte, the youngest brother of Napoleon I.
-
C.
Thibault
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
-
D.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
E.
Stéphane
Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b47be08190828a1c0a11d94ce8 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1a06d7c8190b6c38ff6d18a4542 |
completed | March 8, 2026, 7:44 p.m. |
Created at: March 1, 2026, 7:50 p.m.