Triple
T2921969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R (New York City Subway service) |
E78746
|
entity |
| Predicate | lineGroupColor |
P34402
|
FINISHED |
| Object | Broadway Line services |
—
|
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: Broadway Line services | Statement: [R (New York City Subway service), lineGroupColor, Broadway Line services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineGroupColor Context triple: [R (New York City Subway service), lineGroupColor, Broadway Line services]
-
A.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
B.
lineLetterColorStandard
Indicates the standard or default color assigned to the letter representation of a particular line.
-
C.
hasLineGroup
Indicates that one entity is associated with, or belongs to, a particular group or collection of lines.
-
D.
lineSymbol
Indicates that one entity is used as a line-style or line-representation symbol for another entity.
-
E.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
- 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.