Triple

T14051868
Position Surface form Disambiguated ID Type / Status
Subject Mumbai Island E338110 entity
Predicate contains P35 FINISHED
Object Matunga
Matunga is a central Mumbai neighborhood known for its strong South Indian cultural presence, educational institutions, and historic residential character.
 E1078808 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: Matunga | Statement: [Mumbai Island, contains, Matunga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Matunga
Context triple: [Mumbai Island, contains, Matunga]
  • A. Mangini
    Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
  • B. Manyanga
    Manyanga was an important historical settlement in present-day Zimbabwe that served as the capital of the Rozvi Empire.
  • C. Munja
    Munja, also known as Vakpati Munja, was a prominent 10th-century Paramara king of Malwa celebrated for his military campaigns, patronage of learning, and contributions to early medieval Indian culture.
  • D. Kasangati
    Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
  • E. Matong
    Matong is a small rural locality in the Riverina region of New South Wales, Australia, known for its grain farming and surrounding agricultural landscape.
  • 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: Matunga
Triple: [Mumbai Island, contains, Matunga]
Generated description
Matunga is a central Mumbai neighborhood known for its strong South Indian cultural presence, educational institutions, and historic residential character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Matunga
Target entity description: Matunga is a central Mumbai neighborhood known for its strong South Indian cultural presence, educational institutions, and historic residential character.
  • A. Mangini
    Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
  • B. Manyanga
    Manyanga was an important historical settlement in present-day Zimbabwe that served as the capital of the Rozvi Empire.
  • C. Munja
    Munja, also known as Vakpati Munja, was a prominent 10th-century Paramara king of Malwa celebrated for his military campaigns, patronage of learning, and contributions to early medieval Indian culture.
  • D. Kasangati
    Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
  • E. Matong
    Matong is a small rural locality in the Riverina region of New South Wales, Australia, known for its grain farming and surrounding agricultural landscape.
  • 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_69d81c664e48819088cbd8f433aeffe5 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8bc54c8190a12f0fc056568538 completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb65e63b48190bd5bd4a36cd15396 completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc76f99808190945fd3621fc183ff completed May 7, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_69fcc807cdc48190a3b9dd940d17dc83 completed May 7, 2026, 5:12 p.m.
Created at: April 9, 2026, 10:20 p.m.