Triple
T6343631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Avenue Express (2) |
E142691
|
entity |
| Predicate | serviceTypeInManhattan |
P43857
|
FINISHED |
| Object | express |
—
|
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: express | Statement: [Lexington Avenue Express (2), serviceTypeInManhattan, express]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceTypeInManhattan Context triple: [Lexington Avenue Express (2), serviceTypeInManhattan, express]
-
A.
manhattanServiceType
chosen
Indicates the specific category or type of service provided within the Manhattan area.
-
B.
servicePatternBronx
Indicates a service pattern that specifically applies to or operates within the Bronx.
-
C.
brooklynServiceType
Indicates a relationship where a specified type or category of service is associated with Brooklyn.
-
D.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
E.
serviceOf
Indicates that one entity performs, provides, or fulfills a function or duty on behalf 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0674702d08190806ef0998960b797 |
completed | March 22, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.