Triple
T31797553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 75th Avenue station |
E811637
|
entity |
| Predicate | hasMezzanineType |
P3741
|
FINISHED |
| Object | full-length mezzanine |
—
|
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: full-length mezzanine | Statement: [75th Avenue station, hasMezzanineType, full-length mezzanine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMezzanineType Context triple: [75th Avenue station, hasMezzanineType, full-length mezzanine]
-
A.
hasMezzanine
chosen
Indicates that one entity includes or is equipped with a mezzanine level in relation to another entity.
-
B.
hasCeilingType
Indicates that an entity is associated with or characterized by a specific type of ceiling.
-
C.
hasMinaretType
Indicates that an entity possesses a minaret characterized by a specific architectural or structural type.
-
D.
hasBasementFeature
Indicates that a property’s basement includes or is characterized by a specific feature or attribute.
-
E.
hasMotherhouseType
Indicates the specific type or classification of a religious community’s motherhouse associated with 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_69f348e70d188190b4637c5509f81274 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: April 30, 2026, 11:41 p.m.