Triple
T26729535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Racecourse |
E673927
|
entity |
| Predicate | hasDirtCourse |
P178767
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tokyo Racecourse, hasDirtCourse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirtCourse Context triple: [Tokyo Racecourse, hasDirtCourse, yes]
-
A.
hasOuterTurfCourse
Indicates that a location or facility includes an outer turf (grass) course as part of its layout or structure.
-
B.
hasStraightCourse
Indicates that something follows a direct, uncurved path or progression without significant deviation.
-
C.
hasParCourse
Indicates that an entity is associated with, or includes, a specific par course (an exercise or fitness trail with designated stations).
-
D.
hasRaceSurface
Indicates that an event or activity takes place on, or is associated with, a specific type of race surface.
-
E.
hasNotableFeatureAlongCourse
Indicates that something possesses a notable or distinguishing feature at some point along its course or path.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 27, 2026, 3:44 a.m.