Triple
T614078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuhan Yangtze River Bridge |
E12163
|
entity |
| Predicate | numberOfRailwayTracks |
P17128
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Wuhan Yangtze River Bridge, numberOfRailwayTracks, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRailwayTracks Context triple: [Wuhan Yangtze River Bridge, numberOfRailwayTracks, 2]
-
A.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
C.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
D.
numberOfTrainsInvolved
Indicates the count of trains that are involved in a particular event, situation, or incident.
-
E.
railwayUse
Indicates that something is used as, or functions in the capacity of, a railway or rail-based transportation facility.
- F. None of above. chosen
Provenance (4 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e0a0f588190b953fdb585263307 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfbcbf88190a854921dc531eba8 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.