Triple
T13266189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 170th Street (Grand Concourse) station |
E315929
|
entity |
| Predicate | hasNameTabletMosaics |
P37521
|
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: [170th Street (Grand Concourse) station, hasNameTabletMosaics, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameTabletMosaics Context triple: [170th Street (Grand Concourse) station, hasNameTabletMosaics, yes]
-
A.
hasMosaicNameTablet
chosen
Indicates that an entity is associated with, or possesses, a tablet that bears the name used in a mosaic.
-
B.
hasMemorialTabletsFor
Indicates that one entity contains or displays memorial tablets dedicated to another entity.
-
C.
hasMosaic
Indicates that one entity possesses, contains, or is decorated with a mosaic.
-
D.
hasMosaicsBy
Indicates that something contains or features mosaics that were created by a specified agent or creator.
-
E.
hasMesa
Indicates that an entity possesses, contains, or is associated with a mesa (a flat-topped elevated landform).
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.