Triple
T32958662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Marks |
E843173
|
entity |
| Predicate | hasGallerySpaceIn |
P94044
|
FINISHED |
| Object | New York City |
—
|
NE NERFINISHED |
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: New York City | Statement: [Matthew Marks, hasGallerySpaceIn, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGallerySpaceIn Context triple: [Matthew Marks, hasGallerySpaceIn, New York City]
-
A.
hasGallery
Indicates that one entity possesses, contains, or is associated with a gallery, such as a collection or display space.
-
B.
hasGalleryLocation
chosen
Indicates that an entity is associated with a specific gallery location where it is displayed, stored, or made accessible.
-
C.
hasGalleryLevel
Indicates that an entity is associated with a specific gallery level or floor within a building or exhibition space.
-
D.
hasViewingGallery
Indicates that one entity includes or provides a designated area from which another entity can be observed or viewed.
-
E.
hasPerspectiveGalleryLength
Indicates the length measurement associated with a perspective gallery in a given context or structure.
- 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_69f3494af2808190ad98cec2f1bc0fe6 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:21 a.m.