Triple
T15395591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trolley Museum of New York |
E368168
|
entity |
| Predicate | hasApproximateRouteLength |
P78936
|
FINISHED |
| Object | 1.5 miles |
—
|
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: 1.5 miles | Statement: [Trolley Museum of New York, hasApproximateRouteLength, 1.5 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateRouteLength Context triple: [Trolley Museum of New York, hasApproximateRouteLength, 1.5 miles]
-
A.
approximateRouteLength
chosen
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
-
B.
hasTunnelLengthApprox
Indicates that an entity has a tunnel whose length is approximately a specified value.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
approximateCircuitLengthMi
Indicates the approximate total length of a circuit, measured in miles.
-
E.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ac79081908ac79c0b3e7587ff |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.