Triple
T38366337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ba-Vi |
E892452
|
entity |
| Predicate | countryClub2 |
P64951
|
FINISHED |
| Object | Brazil |
E19289
|
NE 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: Brazil | Statement: [Ba-Vi, countryClub2, Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryClub2 Context triple: [Ba-Vi, countryClub2, Brazil]
-
A.
countryClubType
Indicates that one entity is classified as a specific type or category of country club in relation to another entity.
-
B.
countryClubSetting
Indicates a setting or context that takes place within or is characteristic of a country club environment.
-
C.
homeCountryClub
Indicates that a country club is the primary or official club associated with a particular person or entity as their home club.
-
D.
hasCountryClubLocation
chosen
Indicates that a country club is located at, or associated with, a specific geographic place or address.
-
E.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
- F. None of above.
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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41b28e15788190acceb5d2635dc7a0 |
completed | June 28, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.