Triple
T21586503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Plaza |
E532663
|
entity |
| Predicate | plannedMuseumComponent |
P87179
|
FINISHED |
| Object | contemporary art galleries |
—
|
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: contemporary art galleries | Statement: [Museum Plaza, plannedMuseumComponent, contemporary art galleries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedMuseumComponent Context triple: [Museum Plaza, plannedMuseumComponent, contemporary art galleries]
-
A.
hasMuseumComponent
chosen
Indicates that something includes, contains, or is composed of a museum or museum-related part as one of its components.
-
B.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
-
C.
museumHolds
Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
-
D.
museumCity
Indicates the city in which a given museum is located.
-
E.
operatesMuseum
Indicates that one entity manages and runs the day-to-day operations of a museum.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb6137fc8190840b7c1275e62a1d |
completed | April 27, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:31 p.m.