Triple
T9909829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicolas Anelka |
E185111
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nicolas |
E28979
|
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: Nicolas | Statement: [Nicolas Anelka, givenName, Nicolas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Context triple: [Nicolas Anelka, givenName, Nicolas]
-
A.
Nicholas
chosen
Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
-
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.
Ludovic
Ludovic is a masculine given name, used in various European languages, that is etymologically related to the name Ludwig.
-
D.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
E.
Phillippe
Phillippe is a given name and surname, typically a French-influenced variant of Philip, used for both real and fictional individuals.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb51184d08190a0350f2722110811 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20db5979081909b8e292ac6bb7c2f |
completed | April 5, 2026, 7:22 a.m. |
Created at: March 30, 2026, 8:41 p.m.