Triple
T12619217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurent Blanc |
E301335
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Alès |
E103781
|
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: Alès | Statement: [Laurent Blanc, placeOfBirth, Alès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alès Context triple: [Laurent Blanc, placeOfBirth, Alès]
-
A.
Alès
chosen
Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
-
B.
Abriès
Abriès is a small alpine commune in southeastern France, known for its scenic location in the Queyras valley near the Italian border and its outdoor mountain activities.
-
C.
Vidourle
Vidourle is a river in southern France that flows through the Gard department before emptying into the Mediterranean Sea.
-
D.
Reyssouze
Reyssouze is a river in eastern France that flows through the Ain department and the town of Bourg-en-Bresse.
-
E.
Aigues-Mortais
Aigues-Mortais are the inhabitants of Aigues-Mortes, a historic fortified town in the Occitanie region of southern France.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c75c9c819092265ebc2b39f21d |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6686d770881909850ffaf820171d9 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:13 p.m.