Triple
T22683896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuller Street, Brockton, Massachusetts |
E560857
|
entity |
| Predicate | hasNearbyMuseumType |
P145776
|
FINISHED |
| Object | contemporary art museum |
—
|
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 museum | Statement: [Fuller Street, Brockton, Massachusetts, hasNearbyMuseumType, contemporary art museum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMuseumType Context triple: [Fuller Street, Brockton, Massachusetts, hasNearbyMuseumType, contemporary art museum]
-
A.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
B.
hasMuseumAt
Indicates that a museum is located at or exists in a specified place or location.
-
C.
hasNearbyExhibits
Indicates that one entity has other exhibits located in close physical proximity to it.
-
D.
nearCulturalInstitution
chosen
Indicates that one entity is located close to, or in the immediate vicinity of, a cultural institution such as a museum, theater, gallery, or similar venue.
-
E.
hasMuseumComponent
Indicates that something includes, contains, or is composed of a museum or museum-related part as one of its components.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1786204d88190a837a5f04e16e94c |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:12 p.m.