Triple
T13810111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayview Stadium |
E331865
|
entity |
| Predicate | hasMainStandOn |
P111564
|
FINISHED |
| Object | north 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: north side | Statement: [Bayview Stadium, hasMainStandOn, north side]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainStandOn Context triple: [Bayview Stadium, hasMainStandOn, north side]
-
A.
hasStand
Indicates that an entity possesses, is equipped with, or is supported by a stand or base structure.
-
B.
hasStandsOn
Indicates that one entity is physically supported by and in contact with the upper surface of another entity.
-
C.
hasStandsType
Indicates that an entity has or is associated with a particular type or category of stands (e.g., display stands, support stands, or similar structures).
-
D.
mainStandName
Indicates that one entity is the primary or official name of a stand associated with another entity.
-
E.
hasStandsOnAllSides
Indicates that one entity completely surrounds and is positioned on every side of another entity.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026ff6b481908066d6bf27064417 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:12 p.m.