Triple
T14737367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing–Tianjin Intercity Railway |
E346247
|
entity |
| Predicate | lineNumberOfStations |
P1301
|
FINISHED |
| Object | multiple intermediate stations |
—
|
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: multiple intermediate stations | Statement: [Beijing–Tianjin Intercity Railway, lineNumberOfStations, multiple intermediate stations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineNumberOfStations Context triple: [Beijing–Tianjin Intercity Railway, lineNumberOfStations, multiple intermediate stations]
-
A.
numberOfStations
chosen
Indicates the total count of stations associated with or contained by a given entity.
-
B.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
C.
numberOfRailLines
Indicates the total count of rail lines associated with or serving a given entity.
-
D.
railwayLineLength
Indicates the total measured length of a railway line.
-
E.
maximumStationsPerSegment
Indicates the greatest number of stations that are allowed or can exist within a single segment.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec73264848190be23c5f0260cbe13 |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:29 a.m.