Triple
T36679377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Stand |
E905633
|
entity |
| Predicate | belongsToVenueType |
P10640
|
FINISHED |
| Object | sports stadium |
—
|
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: sports stadium | Statement: [East Stand, belongsToVenueType, sports stadium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToVenueType Context triple: [East Stand, belongsToVenueType, sports stadium]
-
A.
refersToVenueType
chosen
Indicates that one entity specifies or identifies the type or category of venue associated with another entity.
-
B.
hasVenueComponentType
Indicates that a venue is associated with a specific type of component or functional part it contains or comprises.
-
C.
belongsToCampaignType
Indicates that something is associated with or classified under a specific campaign type.
-
D.
locatedInVenueType
Indicates that an entity is situated within or associated with a venue of a specific type (e.g., stadium, theater, restaurant).
-
E.
belongsToStadiumType
Indicates that a stadium is classified as being of a particular stadium type.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fff09dae088190bd8460060d778feb |
completed | May 10, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69fff0027c5c8190baa5c7a15852cbe0 |
completed | May 10, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:12 p.m.