Triple
T28249975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRT (A Division) lines |
E712285
|
entity |
| Predicate | hasOriginalSegment |
P102901
|
FINISHED |
| Object | City Hall–145th Street line |
—
|
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–145th Street line | Statement: [IRT (A Division) lines, hasOriginalSegment, City Hall–145th Street line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalSegment Context triple: [IRT (A Division) lines, hasOriginalSegment, City Hall–145th Street line]
-
A.
hasOriginalPart
chosen
Indicates that an entity includes a component or segment that is part of its initial, original composition.
-
B.
hasSegmentFrom
Indicates that something includes or contains a segment that originates from or is derived from another specified source.
-
C.
hasOriginalPrefix
Indicates that an entity retains or is associated with its initial or primary prefix from which later forms or variants are derived.
-
D.
hasExplicitOriginal
Indicates that something has a clearly specified, directly stated original source or version from which it is derived.
-
E.
hasOriginalComposition
Indicates that one entity is the initial or primary compositional source or makeup of another 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 27, 2026, 11:04 p.m.