Triple
T28003802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rookery Stand |
E707217
|
entity |
| Predicate | roleAtStadium |
P167794
|
FINISHED |
| Object | major home stand |
—
|
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: major home stand | Statement: [Rookery Stand, roleAtStadium, major home stand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtStadium Context triple: [Rookery Stand, roleAtStadium, major home stand]
-
A.
cityStadiumRole
Indicates that a city serves a particular role or function in relation to a stadium, such as hosting, owning, or being the primary location for it.
-
B.
roleAtSportsTeam
Indicates the specific position or function an individual holds within a sports team.
-
C.
roleAtMatches
Indicates that an entity’s role or position at a given time or context matches a specified role criterion.
-
D.
roleAtTheAthletic
Indicates that an entity holds or held a specific role or position at The Athletic.
-
E.
roleInSoccer
Indicates the specific function or position an entity holds within the context of playing or organizing a soccer game.
- 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_69ef96ba350c81908230d0b501b974c4 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f66cf092c881908d7034c9c2bc61d5 |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 27, 2026, 7:58 p.m.