Triple
T26887590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PESCARA C.LE |
E677083
|
entity |
| Predicate | codeForStationName |
P57454
|
FINISHED |
| Object | Pescara Centrale |
—
|
NE NERFINISHED |
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: Pescara Centrale | Statement: [PESCARA C.LE, codeForStationName, Pescara Centrale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeForStationName Context triple: [PESCARA C.LE, codeForStationName, Pescara Centrale]
-
A.
codeForStationIn
Indicates that a specific code is assigned to or used to identify a station within a particular system, network, or context.
-
B.
railwayStationCodeFor
chosen
Indicates that one entity is the designated railway station code corresponding to a particular railway station.
-
C.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
D.
railroadCodeFor
Indicates that a specific railroad code is assigned to or used to identify a particular railroad entity.
-
E.
railwayStationCodeCountry
Indicates that a specific railway station code is associated with a particular country.
- 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_69eee9bc0c90819085608c8bdc513a57 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61f65926c8190a7028986658e966e |
completed | May 2, 2026, 3:59 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:43 a.m.