Triple
T6690327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trans-Hudson rail network |
E152607
|
entity |
| Predicate | hasDirectionOfTravel |
P4069
|
FINISHED |
| Object | bidirectional |
—
|
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: bidirectional | Statement: [Trans-Hudson rail network, hasDirectionOfTravel, bidirectional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectionOfTravel Context triple: [Trans-Hudson rail network, hasDirectionOfTravel, bidirectional]
-
A.
transportDirection
Indicates the directional flow or route along which something is transported from an origin toward a destination.
-
B.
hasTrafficDirection
chosen
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
C.
containsDirectionOf
Indicates that one entity includes or encompasses the directional orientation or path associated with another entity.
-
D.
hasDirectionType
Indicates that something possesses or is associated with a specific type or category of direction.
-
E.
netTransportDirection
Indicates the overall direction in which something (such as material, energy, or information) is being transported when considering all contributing flows together.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.