Triple
T10706382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 11 |
E252416
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object | Belleville |
E333404
|
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: Belleville | Statement: [Paris Métro Line 11, servesStation, Belleville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belleville Context triple: [Paris Métro Line 11, servesStation, Belleville]
-
A.
Belleville
chosen
Belleville is a vibrant, historically working-class neighborhood in northeastern Paris known for its multicultural character, street art, and lively food scene.
-
B.
Belleville
Belleville is a small village in south-central Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
-
C.
Belleville
Belleville is a small Canadian city in southeastern Ontario, known as a regional service and commercial hub on the Bay of Quinte.
-
D.
Belleville valley
Belleville valley is a geographical valley region whose waters are collected and carried away by the Doron de Belleville river in the French Alps.
-
E.
Saint‑Cloud
Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddfbed48190810bb3faee473fde |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998fe56dc8190ae0c987b28ec6206 |
completed | April 11, 2026, 12:42 a.m. |
Created at: April 8, 2026, 9:12 p.m.