Triple
T33426859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biella San Paolo railway station |
E856007
|
entity |
| Predicate | hasStationCodeCountry |
P156564
|
FINISHED |
| Object | Italy |
—
|
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: Italy | Statement: [Biella San Paolo railway station, hasStationCodeCountry, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationCodeCountry Context triple: [Biella San Paolo railway station, hasStationCodeCountry, Italy]
-
A.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
B.
hasStationCodeRole
Indicates that an entity holds or is assigned a specific role associated with a station code within a system or context.
-
C.
hasStationCodeSystem
Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
-
D.
railwayStationCodeCountry
chosen
Indicates that a specific railway station code is associated with a particular country.
-
E.
hasStationCodeInternal
Indicates that an entity is associated with a specific internal station code used within a system or organization.
- 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff49016dcc8190a8a43868c728b4f1 |
completed | May 9, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69ff4891924c8190b5be340e2520e012 |
completed | May 9, 2026, 2:45 p.m. |
Created at: May 1, 2026, 1:36 a.m.