Triple

T10213316
Position Surface form Disambiguated ID Type / Status
Subject Rangeela E242381 entity
Predicate followsCharacter P10688 FINISHED
Object Munna
Munna is a central character in the 1995 Indian film "Rangeela," portrayed as a street-smart, lovable friend whose unspoken love for the heroine drives much of the story’s emotional core.
 E849940 NE FINISHED

How this triple was built (4 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: Munna | Statement: [Rangeela, followsCharacter, Munna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Munna
Context triple: [Rangeela, followsCharacter, Munna]
  • A. Munna
    Munna is a 2007 Indian Telugu-language action drama film starring Prabhas as a college student seeking revenge against a powerful mafia leader.
  • B. Munmun
    Munmun is a satirical young adult novel by Jesse Andrews that explores extreme economic inequality through a fantastical world where people’s physical size reflects their wealth.
  • C. Babla
    Babla is an influential chutney music artist known for helping popularize the genre through his energetic, Indo-Caribbean–inspired recordings and performances.
  • D. Babla
    Babla is an individual known primarily as the spouse of Kanchan.
  • E. Naman
    Naman is an endangered Oceanic language spoken by a small community in Vanuatu.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Munna
Triple: [Rangeela, followsCharacter, Munna]
Generated description
Munna is a central character in the 1995 Indian film "Rangeela," portrayed as a street-smart, lovable friend whose unspoken love for the heroine drives much of the story’s emotional core.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Munna
Target entity description: Munna is a central character in the 1995 Indian film "Rangeela," portrayed as a street-smart, lovable friend whose unspoken love for the heroine drives much of the story’s emotional core.
  • A. Munna
    Munna is a 2007 Indian Telugu-language action drama film starring Prabhas as a college student seeking revenge against a powerful mafia leader.
  • B. Munmun
    Munmun is a satirical young adult novel by Jesse Andrews that explores extreme economic inequality through a fantastical world where people’s physical size reflects their wealth.
  • C. Babla
    Babla is an influential chutney music artist known for helping popularize the genre through his energetic, Indo-Caribbean–inspired recordings and performances.
  • D. Babla
    Babla is an individual known primarily as the spouse of Kanchan.
  • E. Naman
    Naman is an endangered Oceanic language spoken by a small community in Vanuatu.
  • F. None of above. chosen

Provenance (5 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa24efc081909714d98943543283 completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d652ea80dc81908bc65ee2ec390467 completed April 8, 2026, 1:06 p.m.
NEDg Description generation batch_69d657818b008190a24170717cff53b9 completed April 8, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69d65835a11c819083d069ab0f644d4c completed April 8, 2026, 1:29 p.m.
Created at: April 6, 2026, 11:03 a.m.