Triple
T39029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William |
E772
|
entity |
| Predicate | cognate |
P2527
|
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: [William, cognate, Guillaume]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guillaume Context triple: [William, cognate, Guillaume]
-
A.
Guillaume
chosen
Guillaume is the French form of the given name William, commonly used in French-speaking countries.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Stephen Sauvestre
Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
-
D.
Jean-Baptiste
Jean-Baptiste is the French given name of the mathematician and physicist Jean-Baptiste Joseph Fourier, known for pioneering Fourier analysis and the study of heat conduction.
-
E.
Charles Léon
Charles Léon was the illegitimate son of Napoleon Bonaparte and a French servant, known primarily for his connection to the emperor.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ec1ef5481909daf99654dfa3f57 |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2b85b11c08190b97de9b0382be6d5 |
completed | Feb. 28, 2026, 9:41 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.