Triple
T21653170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taichung Metropolitan Opera House |
E534390
|
entity |
| Predicate | numberOfMainTheaters |
P2427
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Taichung Metropolitan Opera House, numberOfMainTheaters, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainTheaters Context triple: [Taichung Metropolitan Opera House, numberOfMainTheaters, 3]
-
A.
hasNumberOfTheatres
chosen
Indicates the quantity of theatres associated with or present in a given entity.
-
B.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
C.
numberOfHalls
Indicates the quantity of halls associated with a given entity or location.
-
D.
hasOperatingTheatres
Indicates that an entity possesses or includes one or more operating theatres as part of its facilities or infrastructure.
-
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.
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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59164fe081908abd2e33dcd67def |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.