Triple
T10897637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maitreyi Ramakrishnan |
E257351
|
entity |
| Predicate | voicedCharacter |
P2000
|
FINISHED |
| Object | Priya Mangal |
E256028
|
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: Priya Mangal | Statement: [Maitreyi Ramakrishnan, voicedCharacter, Priya Mangal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Priya Mangal Context triple: [Maitreyi Ramakrishnan, voicedCharacter, Priya Mangal]
-
A.
Priya Mangal
chosen
Priya Mangal is a laid-back, deadpan, and loyal member of Mei Lee’s friend group in Pixar’s animated film "Turning Red."
-
B.
Richa Chadha
Richa Chadha is an Indian actress known for her critically acclaimed performances in Hindi films such as "Gangs of Wasseypur" and "Masaan."
-
C.
Radhika Puri Rajan
Radhika Puri Rajan is an Indian academic and writer, known for her work in development studies and as the wife of economist and former RBI Governor Raghuram Rajan.
-
D.
Sarika Thakur
Sarika Thakur, known mononymously as Sarika, is an Indian actress and former child star recognized for her work in Hindi cinema and television.
-
E.
Indira Varma
Indira Varma is a British actress known for her versatile roles in television, film, and theatre, including prominent performances in series such as "Game of Thrones" and "Luther."
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75d03a3fc81908df039b9b5ab9ca2 |
completed | April 9, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23b9e5ddc81908cbd27e8db49dbaf |
completed | April 17, 2026, 1:54 p.m. |
Created at: April 8, 2026, 9:21 p.m.