Triple
T13143226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Turgeon |
E312266
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Turgeon |
E773475
|
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: Turgeon | Statement: [Pierre Turgeon, familyName, Turgeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turgeon Context triple: [Pierre Turgeon, familyName, Turgeon]
-
A.
Turgeon
chosen
Turgeon is a French-origin surname borne by various notable individuals, including athletes, coaches, and public figures.
-
B.
Scarphe
Scarphe is a figure from Greek mythology known primarily as the wife of Aeson, the father of the hero Jason.
-
C.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
D.
Juprelle
Juprelle is a municipality in the province of Liège in Wallonia, Belgium, known for its rural character and proximity to the city of Liège.
-
E.
Taconnaz
Taconnaz is a locality in the Chamonix valley of the French Alps, known for giving its name to the nearby Glacier de Taconnaz.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981d24da48190b99e713878e8d003 |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eae4a87881908be57e15f001c904 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 9:10 p.m.