Triple
T2245611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Valence |
E49494
|
entity |
| Predicate | hasSeat |
P3522
|
FINISHED |
| Object | Valence |
E8671
|
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: Valence | Statement: [Arrondissement of Valence, hasSeat, Valence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valence Context triple: [Arrondissement of Valence, hasSeat, Valence]
-
A.
Valence
chosen
Valence is a historic city in southeastern France known as a key cultural and commercial center in the Drôme department.
-
B.
Vals
Vals is a Swiss Alpine village in the canton of Graubünden, renowned for its hot springs and Peter Zumthor’s iconic Therme Vals spa complex.
-
C.
Valor
Valor is a concept or quality associated with courage and bravery in the context of warfare and heroic action.
-
D.
Val
Val is the Allied reporting name for the Aichi D3A, a Japanese World War II carrier-based dive bomber used prominently in early Pacific naval battles.
-
E.
Joy
"Joy" is a 2015 biographical comedy-drama film starring Jennifer Lawrence as a struggling single mother who becomes a successful inventor and entrepreneur.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ea75d881909d4e176a432f32e8 |
completed | March 7, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af989e2cf48190b9c5d053491e3a96 |
completed | March 10, 2026, 4:05 a.m. |
Created at: March 4, 2026, 7:47 p.m.