Triple
T24143939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeonju Kim clan |
E598320
|
entity |
| Predicate | usesBonGwanSystem |
P155003
|
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: [Jeonju Kim clan, usesBonGwanSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBonGwanSystem Context triple: [Jeonju Kim clan, usesBonGwanSystem, yes]
-
A.
bowlSystem
Indicates a relationship where one entity functions as or belongs to a bowling-related system, setup, or arrangement involving bowls or bowling equipment.
-
B.
hasGymSystem
Indicates that an entity is equipped with or utilizes a particular gym or fitness system.
-
C.
hasGondola
Indicates that one entity possesses, includes, or is equipped with a gondola.
-
D.
hasWaka
Indicates that an entity possesses, contains, or is associated with a waka (such as a traditional canoe, vessel, or similarly defined object).
-
E.
boonDetails
Indicates the specific terms, conditions, or characteristics associated with a granted benefit or favor within the relationship or action.
- 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_69e288c9e488819093dd1acd91b08b8a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e008efbc8190ac6c12d3ba5dd5d8 |
completed | April 29, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 11:29 p.m.