Triple
T6964605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | d’Esmier d’Olbreuse family |
E161455
|
entity |
| Predicate | hasSurnameForm |
P18
|
FINISHED |
| Object | d’Olbreuse |
E255693
|
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: d’Olbreuse | Statement: [d’Esmier d’Olbreuse family, hasSurnameForm, d’Olbreuse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: d’Olbreuse Context triple: [d’Esmier d’Olbreuse family, hasSurnameForm, d’Olbreuse]
-
A.
Olbreuse
chosen
Olbreuse is a small locality in western France historically notable as the ancestral seat of the noble d’Olbreuse family.
-
B.
Reyssouze
Reyssouze is a river in eastern France that flows through the Ain department and the town of Bourg-en-Bresse.
-
C.
La Bresse
La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
-
D.
Aigues-Mortais
Aigues-Mortais are the inhabitants of Aigues-Mortes, a historic fortified town in the Occitanie region of southern France.
-
E.
Riorges
Riorges is a commune in central France, near Roanne in the Loire department, known for its residential character and local cultural life.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daf2b7bc8190a3e73f3b24f0352b |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eeb79b9c819084738c207aa5c62d |
completed | March 28, 2026, 3:07 p.m. |
Created at: March 27, 2026, 2:30 p.m.