Triple
T16864505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Station Park |
E410003
|
entity |
| Predicate | hasStadiumSide |
P125276
|
FINISHED |
| Object | Main Stand side |
—
|
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: Main Stand side | Statement: [Station Park, hasStadiumSide, Main Stand side]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStadiumSide Context triple: [Station Park, hasStadiumSide, Main Stand side]
-
A.
hasCitySide
Indicates that one entity is located on or corresponds to a particular side or area of a city relative to another entity.
-
B.
containsStadium
Indicates that a location or area includes a stadium within its boundaries or premises.
-
C.
hasTeamStadium
Indicates that a sports team is associated with or plays its home games at a particular stadium.
-
D.
hasTeamSide
Indicates that an entity is associated with or belongs to a particular side or faction of a team within a competitive or collaborative context.
-
E.
hasHostStadiumTeam
Indicates that a particular team is the primary host or home team for events held at a given stadium.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b505a390819097ec31cd210eca60 |
completed | April 18, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:24 a.m.