Triple
T6107305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georges St-Pierre |
E136147
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Georges |
E18182
|
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: Georges | Statement: [Georges St-Pierre, givenName, Georges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georges Context triple: [Georges St-Pierre, givenName, Georges]
-
A.
Georges
chosen
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
B.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
C.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
D.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
-
E.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b81fad081909b622cafc6d51249 |
completed | March 22, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d4fdd7288190bb9aef680beb906d |
completed | March 27, 2026, 7:05 p.m. |
Created at: March 22, 2026, 4:13 p.m.