Triple
T18612665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezons |
E454934
|
entity |
| Predicate | statisticalArea |
P15840
|
FINISHED |
| Object | aire d’attraction de Paris |
—
|
NE NERFINISHED |
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: aire d’attraction de Paris | Statement: [Bezons, statisticalArea, aire d’attraction de Paris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: aire d’attraction de Paris Context triple: [Bezons, statisticalArea, aire d’attraction de Paris]
-
A.
aire urbaine de Paris
chosen
The "aire urbaine de Paris" is the vast metropolitan area centered on Paris, encompassing the city and its surrounding suburbs and commuter zones that form France’s largest urban and economic hub.
-
B.
Parisii
The Parisii were a Celtic tribe of the Iron Age and Roman period who lived in the area of present-day Paris along the Seine River.
-
C.
Parigi
Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
-
D.
Parigi
Parigi is a town located in the Vikarabad district of the Indian state of Telangana.
-
E.
Paris 2
Paris 2 is the commonly used short name for Université Paris 2 Panthéon-Assas, a prestigious French university renowned for its programs in law and social sciences.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d030d488190a992d10d3d28b4ad |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 10, 2026, 11:45 a.m.