Triple
T25477173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laverton railway station |
E638463
|
entity |
| Predicate | hasOverpassOrSubway |
P158586
|
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: [Laverton railway station, hasOverpassOrSubway, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOverpassOrSubway Context triple: [Laverton railway station, hasOverpassOrSubway, yes]
-
A.
hasSubway
Indicates that a place is served by or contains a subway (metro) system.
-
B.
hasSubwayComplex
Indicates that one entity contains or is associated with a subway complex as part of its structure or facilities.
-
C.
hasUndergroundConnections
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
-
D.
hasSubwaySymbol
Indicates that one entity is used as the official subway symbol or icon representing another entity.
-
E.
hasSubwayCode
Indicates that an entity is associated with a specific subway system code used to identify it within that transit network.
- F. None of above. chosen
Provenance (4 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f772a0248190a52aef4495a5b0a3 |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 2:26 p.m.