Triple
T3267804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Gex |
E68567
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Gex |
E245709
|
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: Gex | Statement: [arrondissement of Gex, administrativeCenter, Gex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gex Context triple: [arrondissement of Gex, administrativeCenter, Gex]
-
A.
Gex
chosen
Gex is a French commune near the Swiss border that serves as a cross-border residential and commuter hub for the Geneva metropolitan area.
-
B.
Daria
Daria is an animated television series centered on the intelligent, sarcastic teenager Daria Morgendorffer as she navigates high school life with deadpan wit and social commentary.
-
C.
Vixen
Vixen is an American all-female glam metal band best known for their late-1980s hits and self-titled debut album.
-
D.
Vixen
Vixen is one of Santa Claus’s traditional flying reindeer, commonly depicted as part of the team that pulls his sleigh on Christmas Eve.
-
E.
Luella Gear
Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcf9c6c819092f9c618b778b46d |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e83e11f081909d64287c0902124a |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:09 p.m.