Triple
T1200053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studio City, Los Angeles, California, United States |
E25758
|
entity |
| Predicate | zonedFor |
P6793
|
FINISHED |
| Object | residential use |
—
|
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: residential use | Statement: [Studio City, Los Angeles, California, United States, zonedFor, residential use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zonedFor Context triple: [Studio City, Los Angeles, California, United States, zonedFor, residential use]
-
A.
hasZone
chosen
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
C.
locatedInTimeZone
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
-
D.
exampleZoneName
Indicates that an entity is associated with a zone identified by a specific example or placeholder name.
-
E.
followedByTimeZone
Indicates that one time zone chronologically succeeds another in a defined ordering or sequence.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9ec3488190afe35af54efae5e9 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.