Triple
T29110544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway (Downtown Los Angeles) corridor |
E736887
|
entity |
| Predicate | numberOfHistoricTheaters |
P201140
|
FINISHED |
| Object | a dozen (approximate) |
—
|
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: a dozen (approximate) | Statement: [Broadway (Downtown Los Angeles) corridor, numberOfHistoricTheaters, a dozen (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHistoricTheaters Context triple: [Broadway (Downtown Los Angeles) corridor, numberOfHistoricTheaters, a dozen (approximate)]
-
A.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
B.
partOfHistoricalTheater
Indicates that one entity is a component, section, or feature belonging to a historical theater.
-
C.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
D.
historicalTheater
Indicates that an entity is a theater recognized for its historical significance or heritage.
-
E.
hasOperatingTheatres
Indicates that an entity possesses or includes one or more operating theatres as part of its facilities or infrastructure.
- F. None of above. chosen
Provenance (4 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69ffcc6182b48190afb598ced6500e66 |
completed | May 10, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69ffcbb363748190bc6f8d038fba44ff |
completed | May 10, 2026, 12:05 a.m. |
| PDg | Predicate description generation | batch_69ffcc60dae48190b76b3eb7e2ce5103 |
completed | May 10, 2026, 12:08 a.m. |
Created at: April 28, 2026, 11:18 a.m.