Triple
T32039701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron White |
E818186
|
entity |
| Predicate | hasDistinctiveProp |
P18160
|
FINISHED |
| Object | cigar |
—
|
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: cigar | Statement: [Ron White, hasDistinctiveProp, cigar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctiveProp Context triple: [Ron White, hasDistinctiveProp, cigar]
-
A.
hasDistinctFeature
chosen
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
B.
hasDistinctiveShape
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
C.
hasDistinctiveFrameworkWith
Indicates that one entity possesses a unique or distinguishing structural framework in relation to another entity.
-
D.
isDistinctiveGivenNameOf
Indicates that a given name uniquely and distinctively identifies or characterizes a particular entity compared to others.
-
E.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
- 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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: May 1, 2026, 12:19 a.m.