Triple
T15292380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL |
E365558
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Lille Metro |
E114351
|
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: Lille Metro | Statement: [VAL, operatesIn, Lille Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lille Metro Context triple: [VAL, operatesIn, Lille Metro]
-
A.
Lille Metro
chosen
The Lille Metro is a fully automated light metro system serving the city of Lille and its metropolitan area in northern France.
-
B.
Lille tramway
The Lille tramway is a light rail system serving the Lille metropolitan area in northern France, complementing the city’s metro and bus networks.
-
C.
Lyon Metro
Lyon Metro is the rapid transit system serving the French city of Lyon and its suburbs, known for its rubber-tyred lines and integration with the city’s broader public transport network.
-
D.
Marseille metro
The Marseille metro is the rapid transit system serving the city of Marseille, France, providing underground rail connections across key urban areas.
-
E.
Charleroi Metro
Charleroi Metro is a light rail and pre-metro transit system serving the Belgian city of Charleroi and its suburbs.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef899e55c8190b1c26491bf37967a |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:15 a.m.