Triple
T14083013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henri Gouraud |
E338913
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Henri |
E50663
|
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: Henri | Statement: [Henri Gouraud, givenName, Henri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henri Context triple: [Henri Gouraud, givenName, Henri]
-
A.
Henri
chosen
Henri is a given name most famously associated with the French artist Henri Matisse.
-
B.
René
René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
-
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.
Francois
Francois is the given first name of South African rugby union scrum-half Faf de Klerk.
-
E.
Gustave
Gustave is a masculine given name of French origin, famously borne by engineer Gustave Eiffel.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ede40048190b465e909565730c1 |
completed | April 14, 2026, 3:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb676620481908ed2fa5687a21866 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.