Triple
T28249976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRT (A Division) lines |
E712285
|
entity |
| Predicate | hasOriginalTerminal |
P181741
|
FINISHED |
| Object | City Hall station |
—
|
NE NERFINISHED |
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: City Hall station | Statement: [IRT (A Division) lines, hasOriginalTerminal, City Hall station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalTerminal Context triple: [IRT (A Division) lines, hasOriginalTerminal, City Hall station]
-
A.
usedTerminal
Indicates that an entity made use of or interacted with a particular terminal or endpoint device.
-
B.
hasIntegratedTerminal
Indicates that one entity includes or supports a built-in terminal interface as part of its functionality.
-
C.
hasOriginalCompiler
Indicates that one entity is the original creator or compiler responsible for assembling or producing another entity.
-
D.
hasOriginalVersion
Indicates that one entity is the original or initial version from which another entity is derived or adapted.
-
E.
hasOriginalCharacter
Indicates that an entity includes, features, or is associated with an original character distinct from pre-existing or canonical characters.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7824dc3f0819092a5102895b4a478 |
completed | May 3, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f7817c79e081908e685c48165e086b |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 27, 2026, 11:04 p.m.