Triple
T1134738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Avenue Line |
E23112
|
entity |
| Predicate | isBusiestInSystem |
P26423
|
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: [Lexington Avenue Line, isBusiestInSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBusiestInSystem Context triple: [Lexington Avenue Line, isBusiestInSystem, yes]
-
A.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
B.
isOneOfBusiestStopsOn
Indicates that a stop ranks among the most heavily used or frequently served stops on a given route or line.
-
C.
isInUse
Indicates that an entity is currently being utilized or actively engaged in its intended function or operation.
-
D.
isLargestOf
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
-
E.
isMaximumWhen
Indicates that a quantity or function reaches its greatest possible value under specified conditions or at a particular point.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bddfa598819088690e1ab010ba0b |
completed | March 1, 2026, 10:29 p.m. |
Created at: March 1, 2026, 7:44 p.m.