Triple
T27985118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Subway lettered services |
E706723
|
entity |
| Predicate | usesTrainWidth |
P26300
|
FINISHED |
| Object | 10-foot-wide cars |
—
|
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: 10-foot-wide cars | Statement: [New York City Subway lettered services, usesTrainWidth, 10-foot-wide cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainWidth Context triple: [New York City Subway lettered services, usesTrainWidth, 10-foot-wide cars]
-
A.
hasRailWidth
Indicates that one entity has a specified width measurement for its rail or rails.
-
B.
usedForTrainLength
Indicates that something is used to determine, measure, or represent the length of a train.
-
C.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
D.
hasTrainStyle
Indicates that one entity (typically a train or rail service) is characterized by or associated with a particular style, type, or configuration of train.
-
E.
usesCarWidth
chosen
Indicates that one entity determines, measures, or constrains something based on the width of a car.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 7:47 p.m.