Triple
T6965242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillaume Canet |
E161471
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Guillaume |
E16054
|
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: Guillaume | Statement: [Guillaume Canet, givenName, Guillaume]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guillaume Context triple: [Guillaume Canet, givenName, Guillaume]
-
A.
Guillaume
chosen
Guillaume is the French form of the given name William, commonly used in French-speaking countries.
-
B.
Hugues
Hugues is a French given name, equivalent to the English name Hugh, historically borne by various nobles, clerics, and notable figures in French-speaking regions.
-
C.
Gioffre
Gioffre is an Italian given name most notably borne by Gioffre Borgia, a younger son of Pope Alexander VI from the influential Borgia family of Renaissance Italy.
-
D.
Guillaume de Maria
Guillaume de Maria is a film producer known for his work on the French movie "Une enfant du siècle."
-
E.
Raoul
Raoul is a violent, masked intruder and one of the primary antagonists in the thriller film "Panic Room."
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db1049e0819097099a0e9d15f787 |
completed | March 27, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c758a57b8481908cef7de9b3abf7a3 |
completed | March 28, 2026, 4:27 a.m. |
Created at: March 27, 2026, 2:30 p.m.