Triple
T27985153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Subway lettered services |
E706723
|
entity |
| Predicate | includesCBTCSegments |
P197552
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [New York City Subway lettered services, includesCBTCSegments, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCBTCSegments Context triple: [New York City Subway lettered services, includesCBTCSegments, Yes]
-
A.
includesCapSegments
Indicates that an entity contains or is composed of one or more capitalized text segments as part of its structure or content.
-
B.
appearsInSegmentOf
Indicates that one entity occurs within, or is featured as part of, a specific segment or subsection of another entity.
-
C.
hasSegmentBasedOn
Indicates that one segment is derived from, modeled after, or constructed using another segment as its basis.
-
D.
hasExpressSegments
Indicates that a route, service, or path includes segments that are designated as express, skipping certain intermediate stops or steps.
-
E.
controlSegment
Indicates that one entity governs, directs, or regulates a specific segment or portion of another entity or system.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
| PDg | Predicate description generation | batch_69fe9b013ec481908f89beddb9c4cd4e |
completed | May 9, 2026, 2:25 a.m. |
Created at: April 27, 2026, 7:47 p.m.