Triple
T30845078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian American Museum of Los Angeles |
E785608
|
entity |
| Predicate | occupiesFloor |
P2911
|
FINISHED |
| Object | upper floor of Italian Hall |
—
|
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: upper floor of Italian Hall | Statement: [Italian American Museum of Los Angeles, occupiesFloor, upper floor of Italian Hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiesFloor Context triple: [Italian American Museum of Los Angeles, occupiesFloor, upper floor of Italian Hall]
-
A.
occupiesFloorsOf
Indicates that one entity uses or takes up multiple levels or stories within a building or structure.
-
B.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
C.
hasFloorUse
Indicates that a particular floor or level of a building is designated for a specific function, activity, or type of use.
-
D.
occupiedBy
chosen
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
E.
floorAbove
Indicates that one floor is located directly above another floor in a vertical arrangement.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 29, 2026, 8:46 p.m.