Triple
T102039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Series |
E2058
|
entity |
| Predicate | hasPlaySurface |
P1242
|
FINISHED |
| Object | baseball field |
—
|
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: baseball field | Statement: [World Series, hasPlaySurface, baseball field]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaySurface Context triple: [World Series, hasPlaySurface, baseball field]
-
A.
hasSurfaceGravity
Indicates that one entity possesses a specific gravitational acceleration at its surface, typically measured as the strength of gravity experienced at or near that surface.
-
B.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
C.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
D.
hasPlatformType
Indicates that an entity is associated with or characterized by a specific type or category of platform.
-
E.
surfaceType
chosen
Indicates the kind or classification of surface associated with an entity or interaction.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2563921f8819087f720b1c803579f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.