Triple
T20139015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barker family |
E491108
|
entity |
| Predicate | hasNotableCaseType |
P4217
|
FINISHED |
| Object | high-profile kidnappings |
—
|
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: high-profile kidnappings | Statement: [Barker family, hasNotableCaseType, high-profile kidnappings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCaseType Context triple: [Barker family, hasNotableCaseType, high-profile kidnappings]
-
A.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
-
B.
hasNotableType
Indicates that an entity is associated with a specific notable category or type that characterizes its significance or role.
-
C.
hasTypeOfCase
chosen
Indicates that an entity is associated with or classified under a particular type or category of case.
-
D.
notableCaseContext
Indicates that an entity is associated with a particular contextual detail, circumstance, or background information relevant to a notable case or instance.
-
E.
hasNotableJudge
Indicates that an entity is associated with a judge who is distinguished, prominent, or otherwise notable in some recognized way.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667698a188190869c18b925dba2ed |
completed | April 20, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:32 p.m.