Triple
T16273404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peel station (Montreal Metro) |
E395059
|
entity |
| Predicate | depthRankInNetwork |
P1536
|
FINISHED |
| Object | 35 |
—
|
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: 35 | Statement: [Peel station (Montreal Metro), depthRankInNetwork, 35]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depthRankInNetwork Context triple: [Peel station (Montreal Metro), depthRankInNetwork, 35]
-
A.
depthRank
chosen
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
B.
positionInNetwork
Indicates the specific role or location an entity occupies within a network’s structure or topology.
-
C.
heightRankWithinStructure
Indicates the relative ordering of an entity’s height compared to other entities within the same structure.
-
D.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
E.
capacityRank
Indicates the relative ordering of entities based on how much capacity (e.g., volume, throughput, or capability) they possess compared to others.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2460b22d88190bdc7cf509cf74198 |
completed | April 17, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.