Triple
T23992800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Squirrel |
E605111
|
entity |
| Predicate | originOfJoke |
P63937
|
FINISHED |
| Object | Crowley’s habit of giving animal nicknames |
—
|
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: Crowley’s habit of giving animal nicknames | Statement: [Squirrel, originOfJoke, Crowley’s habit of giving animal nicknames]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originOfJoke Context triple: [Squirrel, originOfJoke, Crowley’s habit of giving animal nicknames]
-
A.
humorSource
chosen
Indicates that one entity is the origin or cause of humor experienced in relation to another entity.
-
B.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
C.
originOfCharacter
Indicates the source or place from which a character originates or is created.
-
D.
describesOriginOf
Indicates that one entity specifies or explains the source, provenance, or origin of another entity.
-
E.
punchlineStructure
Indicates the structural role or pattern a punchline follows within a joke or humorous setup.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38ce7fc8190a488991b6f61416b |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:37 p.m.