Triple
T2922048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State station |
E78748
|
entity |
| Predicate | numberOfLinesServed |
P18635
|
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: [State station, numberOfLinesServed, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLinesServed Context triple: [State station, numberOfLinesServed, 2]
-
A.
lineServed
Indicates that a particular transportation line (such as a bus, train, or metro line) provides service to or is operated at a given stop, station, or route segment.
-
B.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
-
C.
servedByLine
Indicates that a transportation stop, station, or location is provided service by a specific transit line.
-
D.
servesLine
Indicates that a transportation stop, station, or facility is on and provides service for a particular transit line.
-
E.
numberOfRailLines
chosen
Indicates the total count of rail lines associated with or serving a given entity.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:54 p.m.