Triple
T21458867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 86th Street (Brooklyn) |
E529415
|
entity |
| Predicate | hasNameTabletStyle |
P37521
|
FINISHED |
| Object | BMT mosaic name tablets |
—
|
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: BMT mosaic name tablets | Statement: [86th Street (Brooklyn), hasNameTabletStyle, BMT mosaic name tablets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameTabletStyle Context triple: [86th Street (Brooklyn), hasNameTabletStyle, BMT mosaic name tablets]
-
A.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
B.
hasMosaicNameTablet
chosen
Indicates that an entity is associated with, or possesses, a tablet that bears the name used in a mosaic.
-
C.
hasStylus
Indicates that an entity possesses or is equipped with a stylus as an accessory or tool.
-
D.
isNotebookOf
Indicates that one entity is a notebook that belongs to, is used by, or is associated with another entity.
-
E.
hasScreenType
Indicates the specific kind or category of screen associated with or used by an 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ed36c08190a5178b2308aca8da |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:08 p.m.