Triple
T2676457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tweety |
E56471
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Granny |
E269712
|
NE 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: Granny | Statement: [Tweety, associatedWith, Granny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Granny Context triple: [Tweety, associatedWith, Granny]
-
A.
Granny
chosen
Granny is a recurring elderly character in the Looney Tunes cartoons, best known as the kindly but sharp-witted owner of Tweety Bird (and often Sylvester’s exasperated caretaker).
-
B.
Granma
Granma is the small yacht that carried Fidel Castro and his revolutionaries from Mexico to Cuba in 1956, becoming a symbol of the Cuban Revolution.
-
C.
Granma
Granma is the official newspaper of the Communist Party of Cuba, known for disseminating government policies, political commentary, and state-approved news.
-
D.
Nannie
Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
-
E.
Grandy
Grandy is a surname of English origin borne by various notable individuals, including figures in military, political, and entertainment fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9b4a70481909d8b8242039c1cf2 |
completed | March 7, 2026, 7:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa0638a9c8190b48ca5aa56eb66ff |
completed | March 10, 2026, 4:38 a.m. |
Created at: March 6, 2026, 9:54 p.m.