Triple
T23676527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elgin railway station |
E584891
|
entity |
| Predicate | hasTypicalDestinations |
P133822
|
FINISHED |
| Object | Inverness |
—
|
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: Inverness | Statement: [Elgin railway station, hasTypicalDestinations, Inverness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalDestinations Context triple: [Elgin railway station, hasTypicalDestinations, Inverness]
-
A.
typicalDestinationAddress
Indicates the address that is most commonly or usually used as the destination for something or someone.
-
B.
hasMajorDestinationCountry
Indicates that an entity has a primary or most significant destination country associated with its movement, export, or flow.
-
C.
hasDestinationRegion
Indicates that something is directed, sent, or intended to arrive at a particular geographic or logical region as its destination.
-
D.
hasInternationalDestinations
Indicates that an entity offers, includes, or is connected to destinations located in foreign countries.
-
E.
hasMainDestination
chosen
Indicates that an entity is primarily intended to go to, serve, or be directed toward a particular destination.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f40c9081908ef0cddb6f0392da |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.