Triple
T3123090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvester |
E65231
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Tweety |
E56471
|
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: Tweety | Statement: [Sylvester, enemyOf, Tweety]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tweety Context triple: [Sylvester, enemyOf, Tweety]
-
A.
Tweety
chosen
Tweety is a small, yellow canary from the Looney Tunes cartoons, best known for outsmarting Sylvester the Cat with a deceptively cute demeanor.
-
B.
Foghorn Leghorn
Foghorn Leghorn is a loud, fast-talking, Southern-accented cartoon rooster from the Looney Tunes series known for his comedic antics and catchphrases.
-
C.
Daffy
Daffy is the colloquial nickname given to the British World War II Boulton Paul Defiant turret fighter aircraft.
-
D.
Daffy Duck
Daffy Duck is a classic Looney Tunes cartoon character known for his zany, self-centered antics and comedic rivalry with characters like Bugs Bunny.
-
E.
Pepé Le Pew
Pepé Le Pew is a romantic, overly confident skunk from the Looney Tunes cartoons, best known for his comedic, French-accented pursuit of love.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52c105c8190b8128e66d9b9e8a0 |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f72c2048190ab2aa40a109f5976 |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.