Triple
T20589486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Jungle Book 2 |
E505876
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Kaa |
—
|
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: Kaa | Statement: [The Jungle Book 2, featuresCharacter, Kaa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaa Context triple: [The Jungle Book 2, featuresCharacter, Kaa]
-
A.
Kaa
chosen
Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
-
B.
Takura
Takura is a rural locality in Queensland, Australia, situated near the community associated with Howard.
-
C.
Nganzai
Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
-
D.
Kaei
Kaei was a Japanese era name (nengō) of the late Edo period, notable for encompassing events such as the arrival of Commodore Perry and the opening of Japan to the West.
-
E.
Kaei
Kaei is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a979e4a48190a948165fb0f3b265 |
completed | April 20, 2026, 10:32 p.m. |
Created at: April 16, 2026, 11:40 a.m.