Triple
T25236702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Creusot TGV station |
E632356
|
entity |
| Predicate | offersConnectionType |
P17471
|
FINISHED |
| Object | intercity high-speed services |
—
|
LITERAL 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: intercity high-speed services | Statement: [Le Creusot TGV station, offersConnectionType, intercity high-speed services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersConnectionType Context triple: [Le Creusot TGV station, offersConnectionType, intercity high-speed services]
-
A.
offersConnectionTo
Indicates that one entity provides or enables access, linkage, or connectivity to another entity.
-
B.
offersServiceType
chosen
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
C.
offersLayerType
Indicates that one entity provides or makes available a specific type of layer to another entity or context.
-
D.
offeringType
Indicates the category or nature of what is being offered in a transaction or interaction (e.g., product, service, or other type of offering).
-
E.
offersPanelType
Indicates that an entity provides or makes available a specific type of panel as part of its offerings.
- F. None of above.
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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 21, 2026, 1:07 p.m.