Triple
T25584406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shot Caller |
E641337
|
entity |
| Predicate | hasDUB |
P160126
|
FINISHED |
| Object | driving under the influence |
—
|
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: driving under the influence | Statement: [Shot Caller, hasDUB, driving under the influence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDUB Context triple: [Shot Caller, hasDUB, driving under the influence]
-
A.
isDubVersionOf
Indicates that one audiovisual work is a dubbed version of another, with its original audio replaced by a different language track while preserving the original content.
-
B.
hasDunes
Indicates that one entity (typically a geographic area or surface) possesses or is characterized by sand dunes.
-
C.
hasPub
Indicates that an entity is associated with, or has access to, a public house (pub) as a related establishment or feature.
-
D.
hasDuneType
Indicates that one entity is characterized by or associated with a specific type or classification of dune.
-
E.
hasQuark
Indicates that one entity possesses, contains, or is composed of the other entity as a quark.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6018f91248190985323d1a678e539 |
completed | May 2, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 21, 2026, 4:15 p.m.