Triple
T12589864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léo Delibes |
E300574
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | La Flèche |
E242466
|
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: La Flèche | Statement: [Léo Delibes, placeOfBirth, La Flèche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Flèche Context triple: [Léo Delibes, placeOfBirth, La Flèche]
-
A.
La Flèche
chosen
La Flèche is a historic town in western France known for its royal heritage, educational institutions, and the renowned Zoo de La Flèche.
-
B.
Fort-de-France
Fort-de-France is the largest city and administrative, economic, and cultural center of the French Caribbean island of Martinique.
-
C.
Saumur
Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
-
D.
Alençon
Alençon is a historic town in northwestern France renowned for its fine lace-making tradition and architectural heritage.
-
E.
Blois
Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954bd5e8c8190a2f233b91682341f |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f70928c8190a872ecb47b8da2c7 |
completed | May 3, 2026, 5:01 p.m. |
Created at: April 9, 2026, 5:06 p.m.