Triple
T9906677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kung Fu Panda |
E185027
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Viper |
E708893
|
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: Viper | Statement: [Kung Fu Panda, featuresCharacter, Viper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viper Context triple: [Kung Fu Panda, featuresCharacter, Viper]
-
A.
Viper
Viper is an informal nickname used by pilots for the F-16 Fighting Falcon, a highly maneuverable multirole fighter aircraft.
-
B.
Viper
Viper is a wooden roller coaster at Six Flags Great America known for its classic out-and-back layout and airtime-focused ride experience.
-
C.
Viper
chosen
Viper is a graceful and skilled green snake kung fu master from the Kung Fu Panda film series, known for her agility, kindness, and combat prowess as a member of the Furious Five.
-
D.
Cobra
Cobra is a 1986 American action thriller film starring Sylvester Stallone as a tough, rule-breaking cop battling a violent crime cult.
-
E.
Cobra
Cobra is a fictional terrorist organization and the primary antagonist faction in the G.I. Joe franchise.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50cf8808190a41e565216712704 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb316a188190a1c7fbe0d1997cf5 |
completed | April 5, 2026, 4:55 a.m. |
Created at: March 30, 2026, 8:41 p.m.