Triple
T3865287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinning Park subway station |
E91835
|
entity |
| Predicate | hasNetworkLength |
P18592
|
FINISHED |
| Object | part of 10.5 km circular route |
—
|
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: part of 10.5 km circular route | Statement: [Kinning Park subway station, hasNetworkLength, part of 10.5 km circular route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNetworkLength Context triple: [Kinning Park subway station, hasNetworkLength, part of 10.5 km circular route]
-
A.
hasNetworkSize
Indicates the total number of nodes, members, or connections that make up a given network.
-
B.
networkLength
chosen
Indicates the total measured extent or distance covered by a network (e.g., of connections, links, or paths).
-
C.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
-
D.
hasTrailLength
Indicates that an entity (such as a trail or route) has a specific measured length.
-
E.
hasTunnelLengthApprox
Indicates that an entity has a tunnel whose length is approximately a specified value.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3a253c81909df7dc0422ff7989 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.