Triple

T7844757
Position Surface form Disambiguated ID Type / Status
Subject Pingali Surana E181895 entity
Predicate name P16 FINISHED
Object Pingali Surana E181895 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: Pingali Surana | Statement: [Pingali Surana, name, Pingali Surana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pingali Surana
Context triple: [Pingali Surana, name, Pingali Surana]
  • A. Pingali Surana chosen
    Pingali Surana was a prominent 16th-century Telugu poet and writer of the Vijayanagara era, renowned for his classical works such as "Kalapurnodayam."
  • B. Kailashey Kelenkari
    "Kailashey Kelenkari" is a popular detective novel in Satyajit Ray’s Feluda series, featuring the sleuth Pradosh C. Mitter investigating a mystery linked to ancient Indian art and heritage.
  • C. Simhadri
    Simhadri is a 2003 Telugu-language action drama film starring Jr. NTR that became one of director S. S. Rajamouli’s early commercial blockbusters.
  • D. Srinatha
    Srinatha was a renowned 14th–15th century Telugu poet and scholar celebrated for his courtly poetry and major contributions to classical Telugu literature.
  • E. Kumar Pallana
    Kumar Pallana was an Indian-American character actor and performer known for his quirky supporting roles in several Wes Anderson films and in Steven Spielberg’s "The Terminal."
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb163d92fc8190a4efcb08d6b3d404 completed March 31, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5ae9758c819091e270343ed289aa completed March 31, 2026, 5:26 a.m.
Created at: March 30, 2026, 4:48 p.m.