Triple
T3493390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gustave Moynier |
E73788
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Moynier |
E73788
|
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: Moynier | Statement: [Gustave Moynier, familyName, Moynier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moynier Context triple: [Gustave Moynier, familyName, Moynier]
-
A.
Moynier
chosen
Moynier is a Swiss surname most notably associated with Gustave Moynier, a co-founder and long-serving president of the International Committee of the Red Cross.
-
B.
Le Moyne
Le Moyne is a French surname notably borne by the colonial Le Moyne family, which produced several prominent explorers and administrators in New France and Louisiana.
-
C.
Meunier
Meunier is a black grape variety primarily used in Champagne production, valued for adding fruitiness and early maturity to sparkling wine blends.
-
D.
Meunier
Meunier is a common French occupational surname, historically referring to a miller.
-
E.
Mistinguett
Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbad51648190b756ad621d6d7df0 |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373c23b188190a927d793b03192dc |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:18 p.m.