Triple
T28203720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibley Parish Council |
E716956
|
entity |
| Predicate | hasHumorousCharacteristic |
P14479
|
FINISHED |
| Object | eccentric council members |
—
|
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: eccentric council members | Statement: [Dibley Parish Council, hasHumorousCharacteristic, eccentric council members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumorousCharacteristic Context triple: [Dibley Parish Council, hasHumorousCharacteristic, eccentric council members]
-
A.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
B.
hasHumorType
chosen
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
C.
humorousTone
Indicates that the related communication, expression, or interaction is characterized by humor, playfulness, or comedic intent.
-
D.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
E.
isHumorousWork
Indicates that a work is intended to be humorous or comedic in nature.
- 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_69efd6b826908190857e6e7dad74ed93 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 10:34 p.m.