Triple
T11676424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 86th Street station (IND Eighth Avenue Line) |
E277502
|
entity |
| Predicate | hasStationNameTablet |
P37521
|
FINISHED |
| Object | “86TH ST” |
—
|
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: “86TH ST” | Statement: [86th Street station (IND Eighth Avenue Line), hasStationNameTablet, “86TH ST”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationNameTablet Context triple: [86th Street station (IND Eighth Avenue Line), hasStationNameTablet, “86TH ST”]
-
A.
hasStationNameElement
Indicates that a station is associated with a specific name component or element used as part of its full station name.
-
B.
hasStationStyle
Indicates that one entity (typically a station) possesses or is characterized by a particular architectural or design style.
-
C.
hasStationIcon
Indicates that an entity is associated with a specific icon used to visually represent a station.
-
D.
hasMosaicNameTablet
chosen
Indicates that an entity is associated with, or possesses, a tablet that bears the name used in a mosaic.
-
E.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a station.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a44504c48190b519765a83ff9c5e |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.