Triple
T4822261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stamford Bridge |
E107736
|
entity |
| Predicate | hasHostedSport |
P59860
|
FINISHED |
| Object | football |
—
|
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: football | Statement: [Stamford Bridge, hasHostedSport, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHostedSport Context triple: [Stamford Bridge, hasHostedSport, football]
-
A.
hasHostedVenue
Indicates that a particular venue has served as the location for hosting a specific event or activity.
-
B.
hasSportingEvent
Indicates that a sporting event is associated with, held at, or organized by a given entity.
-
C.
cohostedSportingEvents
Indicates that two or more entities jointly organized or hosted one or more sporting events together.
-
D.
hasConferenceSport
Indicates that an institution participates in or is associated with a particular sport within a specific athletic conference.
-
E.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.