Triple
T13463205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Part-Dieu |
E311423
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | Part-Dieu |
E487674
|
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: Part-Dieu | Statement: [Part-Dieu, hasStationCode, Part-Dieu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Part-Dieu Context triple: [Part-Dieu, hasStationCode, Part-Dieu]
-
A.
La Part-Dieu
La Part-Dieu is a major business and commercial district in Lyon, France, known for its large shopping center, office towers, and central train station.
-
B.
Quartier Part-Dieu
chosen
Quartier Part-Dieu is Lyon’s main business district, known for its high-rise offices, major shopping center, and one of France’s busiest railway stations.
-
C.
Versailles-Rive-Gauche
Versailles-Rive-Gauche is the former name of the main RER suburban railway station serving the Palace of Versailles and its surrounding area in Versailles, France.
-
D.
Châtelet–Les Halles
Châtelet–Les Halles is a major underground transport hub in central Paris, serving as one of the largest and busiest railway and metro stations in Europe.
-
E.
Invalides
Invalides is a Paris Métro and RER station located near Les Invalides in central Paris, serving as a key transport hub for the surrounding historic and governmental district.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf0d95fc81909d9f73d5315dc7b4 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d37b9988190b8f830fb52586340 |
completed | May 3, 2026, 7:08 p.m. |
Created at: April 9, 2026, 9:41 p.m.