Triple
T33703265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWCA |
E863514
|
entity |
| Predicate | hasAcronymJoke |
P184881
|
FINISHED |
| Object | Organization Without a Cool Acronym |
—
|
NE NERFINISHED |
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: Organization Without a Cool Acronym | Statement: [OWCA, hasAcronymJoke, Organization Without a Cool Acronym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcronymJoke Context triple: [OWCA, hasAcronymJoke, Organization Without a Cool Acronym]
-
A.
acronymExpansion
Indicates that one term is an acronym whose letters stand for the words in another, longer expression.
-
B.
hasHumorFunction
Indicates that something serves a humorous role or purpose, such as eliciting amusement, laughter, or comedic effect.
-
C.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
D.
hasAcronymInTitle
Indicates that the title of an entity includes a shortened form or acronym of another specified term or name.
-
E.
acronymContext
Indicates that one term is used as an acronym specifically within the contextual scope defined by another entity (such as a document, domain, or usage setting).
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b628b17c8190aa058c1a51852a27 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b5cadd308190a864245a21b08f9a |
completed | May 3, 2026, 8:53 p.m. |
Created at: May 1, 2026, 1:43 a.m.