Triple
T26386124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolves' Den |
E663284
|
entity |
| Predicate | typeOfVenueArea |
P190991
|
FINISHED |
| Object | stadium seating section |
—
|
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: stadium seating section | Statement: [Wolves' Den, typeOfVenueArea, stadium seating section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfVenueArea Context triple: [Wolves' Den, typeOfVenueArea, stadium seating section]
-
A.
venueArea
Indicates the physical size or spatial extent of a venue, typically measured in units such as square meters or square feet.
-
B.
typeOfHall
Indicates the specific category or kind to which a particular hall belongs (e.g., lecture hall, dining hall, concert hall).
-
C.
standardArea
Indicates that an entity has a designated or officially defined area or size that serves as a standard reference.
-
D.
areaOf
Indicates that one entity represents the measured surface extent (area) of another entity.
-
E.
floorAreaFeature
Indicates a relationship where a specific feature or characteristic is associated with the floor area of an entity or space.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: April 26, 2026, 11:22 p.m.