Triple
T22012477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Rainbow |
E543610
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Kokila |
—
|
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: Kokila | Statement: [My Rainbow, publisher, Kokila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kokila Context triple: [My Rainbow, publisher, Kokila]
-
A.
Kokila
Kokila is a critically acclaimed Indian film directed by Balu Mahendra, known for its realistic storytelling and evocative cinematography.
-
B.
Kokila
chosen
Kokila is an imprint of Penguin Random House dedicated to publishing diverse, inclusive, and socially conscious books for children and young adults.
-
C.
Kokilaben
Kokilaben is an Indian business matriarch best known as the widow of industrialist Dhirubhai Ambani and the mother of Reliance Group leaders Mukesh and Anil Ambani.
-
D.
Nikiya
Nikiya is the tragic temple dancer heroine of the classical ballet *La Bayadère*, renowned for her ethereal presence and doomed love story.
-
E.
Kilara
Kilara is a spacewoman ally of Gamera who helps protect Earth from alien threats in the film "Gamera: Super Monster."
- 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a5e624819082ed5beeb4bc82fa |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:22 p.m.