Triple
T13407341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blayney railway station |
E319994
|
entity |
| Predicate | hasGoodsShed |
P93321
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Blayney railway station, hasGoodsShed, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGoodsShed Context triple: [Blayney railway station, hasGoodsShed, yes]
-
A.
hasGoodsYard
Indicates that a location or facility includes or is equipped with a goods yard for handling freight or cargo.
-
B.
hasGoodsServices
Indicates that one entity provides, offers, or is associated with specific goods or services in relation to another entity.
-
C.
hasShop
Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
-
D.
sheds
Indicates that one entity naturally loses, discards, or lets fall something from itself, such as hair, skin, leaves, or other material.
-
E.
hasGoodsFacilities
chosen
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4be498819094798473a1bfd853 |
completed | April 12, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:35 p.m.