Triple

T10354174
Position Surface form Disambiguated ID Type / Status
Subject Madhur Mittal E243954 entity
Predicate appearedIn P795 FINISHED
Object Maatr
Maatr is a 2017 Indian revenge thriller film that follows a mother's quest for justice after a brutal crime against her and her daughter.
 E857941 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: Maatr | Statement: [Madhur Mittal, appearedIn, Maatr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maatr
Context triple: [Madhur Mittal, appearedIn, Maatr]
  • A. Meenas
    The Meenas are an indigenous tribal community of northern India, historically associated with agrarian livelihoods, local chieftaincies, and a distinct cultural and religious heritage.
  • B. Kaalpurush
    Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
  • C. Ben Aan
    Ben Aan is a popular, relatively small hill in the Trossachs region of Scotland, known for its steep but short ascent and panoramic views over Loch Katrine and Loch Achray.
  • D. Mankatha
    Mankatha is a 2011 Tamil action-thriller film directed by Venkat Prabhu, known for its heist plot and Ajith Kumar’s anti-hero performance.
  • E. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • 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: Maatr
Triple: [Madhur Mittal, appearedIn, Maatr]
Generated description
Maatr is a 2017 Indian revenge thriller film that follows a mother's quest for justice after a brutal crime against her and her daughter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maatr
Target entity description: Maatr is a 2017 Indian revenge thriller film that follows a mother's quest for justice after a brutal crime against her and her daughter.
  • A. Meenas
    The Meenas are an indigenous tribal community of northern India, historically associated with agrarian livelihoods, local chieftaincies, and a distinct cultural and religious heritage.
  • B. Kaalpurush
    Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
  • C. Ben Aan
    Ben Aan is a popular, relatively small hill in the Trossachs region of Scotland, known for its steep but short ascent and panoramic views over Loch Katrine and Loch Achray.
  • D. Mankatha
    Mankatha is a 2011 Tamil action-thriller film directed by Venkat Prabhu, known for its heist plot and Ajith Kumar’s anti-hero performance.
  • E. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e952c878819084e5d7a593a3f9e9 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750a30af88190b2ebf0daf758ed44 completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618da0188190901026dd51ceaa46 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77045ea988190bd8e31f5f636f69b completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, 11:58 a.m.