Triple
T4595754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lille-Flandres station |
E100199
|
entity |
| Predicate | hasConnection |
P8776
|
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: [Lille-Flandres station, hasConnection, Lille Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lille Metro Context triple: [Lille-Flandres station, hasConnection, 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.
Charleroi Metro
Charleroi Metro is a light rail and pre-metro transit system serving the Belgian city of Charleroi and its suburbs.
-
C.
Rennes Metro
Rennes Metro is the rapid transit system serving the city of Rennes in France, providing urban rail transport across the metropolitan area.
-
D.
Paris Metro
The Paris Metro is the extensive rapid transit system serving Paris and its suburbs, known for its dense network, Art Nouveau station entrances, and central role in the city’s public transportation.
-
E.
Paris Métro Gare de Lyon
Paris Métro Gare de Lyon is a major Parisian underground station and transport hub serving multiple metro and RER lines beneath the Gare de Lyon mainline railway terminal.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd593f25888190a4f219e4da494764 |
completed | March 20, 2026, 2:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfa4552148190be200be028ef3fdd |
completed | March 21, 2026, 1:54 a.m. |
Created at: March 20, 2026, 1:11 p.m.