Triple
T15699235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Czervik |
E380549
|
entity |
| Predicate | countryClubAttitude |
P120351
|
FINISHED |
| Object | disrespectful of decorum |
—
|
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: disrespectful of decorum | Statement: [Al Czervik, countryClubAttitude, disrespectful of decorum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryClubAttitude Context triple: [Al Czervik, countryClubAttitude, disrespectful of decorum]
-
A.
countryClubSetting
Indicates a setting or context that takes place within or is characteristic of a country club environment.
-
B.
hasCountryClubLocation
Indicates that a country club is located at, or associated with, a specific geographic place or address.
-
C.
awayClub
Indicates that one entity is the club playing as the visiting (away) team in a sports match or event relative to another entity.
-
D.
golfCourseUse
Indicates that an entity is used as a golf course or for playing golf.
-
E.
golfCourseStyle
Indicates the design or architectural style that characterizes a particular golf course.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0b4d01c9c81909f6b611e8144c838 |
completed | April 16, 2026, 10:07 a.m. |
Created at: April 10, 2026, 4:44 a.m.