Triple

T4951557
Position Surface form Disambiguated ID Type / Status
Subject Shyam Benegal E111179 entity
Predicate notableWork P4 FINISHED
Object Mammo
Mammo is an acclaimed 1994 Indian drama film directed by Shyam Benegal that explores themes of partition, identity, and displacement through the story of an elderly Muslim woman facing deportation from India.
 E481989 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: Mammo | Statement: [Shyam Benegal, notableWork, Mammo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mammo
Context triple: [Shyam Benegal, notableWork, Mammo]
  • A. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • B. Moll
    Moll is a character in the 1937 pro-labor musical play "The Cradle Will Rock," representing the struggles of the working class under corrupt capitalist forces.
  • C. Moli
    Moli is a settlement located on Choiseul Island in the Solomon Islands.
  • D. MAM
    MAM is a prominent modern art museum in Mexico City known for its extensive collection of 20th- and 21st-century Mexican and international artworks.
  • E. Mēmele
    Mēmele is a river in the Baltic region that serves as one of the headwaters forming Latvia’s Lielupe River.
  • 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: Mammo
Triple: [Shyam Benegal, notableWork, Mammo]
Generated description
Mammo is an acclaimed 1994 Indian drama film directed by Shyam Benegal that explores themes of partition, identity, and displacement through the story of an elderly Muslim woman facing deportation from India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mammo
Target entity description: Mammo is an acclaimed 1994 Indian drama film directed by Shyam Benegal that explores themes of partition, identity, and displacement through the story of an elderly Muslim woman facing deportation from India.
  • A. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • B. Moll
    Moll is a character in the 1937 pro-labor musical play "The Cradle Will Rock," representing the struggles of the working class under corrupt capitalist forces.
  • C. Moli
    Moli is a settlement located on Choiseul Island in the Solomon Islands.
  • D. MAM
    MAM is a prominent modern art museum in Mexico City known for its extensive collection of 20th- and 21st-century Mexican and international artworks.
  • E. Mēmele
    Mēmele is a river in the Baltic region that serves as one of the headwaters forming Latvia’s Lielupe River.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71b561ec81908083225269222e96 completed March 20, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81d3d9548190ae0a34549eb88036 completed March 21, 2026, 11:32 a.m.
NEDg Description generation batch_69be8287c9e481909aed15a20c3a3d20 completed March 21, 2026, 11:35 a.m.
NED2 Entity disambiguation (via description) batch_69be8301bfd88190b82442e17727ae3b completed March 21, 2026, 11:37 a.m.
Created at: March 20, 2026, 1:31 p.m.