Triple
T21096136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Orleans Hotel and Casino |
E519771
|
entity |
| Predicate | hasMovieTheater |
P142832
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Orleans Hotel and Casino, hasMovieTheater, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMovieTheater Context triple: [The Orleans Hotel and Casino, hasMovieTheater, yes]
-
A.
hasNeighbouringTheatre
Indicates that one theatre is located close enough to another theatre to be considered its neighbor.
-
B.
locatedInTheater
Indicates that something is situated within or inside a theater.
-
C.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
D.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
E.
intendedTheater
Indicates the theater or venue that an event, performance, or screening is planned or meant to take place in.
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b595cdc8190ba7a6f3f71d40c3f |
completed | April 21, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69e5dbfcd5e881908f1e4e0d2d237856 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:52 p.m.