Triple

T8558936
Position Surface form Disambiguated ID Type / Status
Subject Roja E202642 entity
Predicate starring P1507 FINISHED
Object Madhoo
Madhoo is an Indian actress best known for her lead role in the critically acclaimed Tamil film "Roja" and her work across multiple Indian film industries.
 E743900 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: Madhoo | Statement: [Roja, starring, Madhoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Madhoo
Context triple: [Roja, starring, Madhoo]
  • A. Mawanella
    Mawanella is a town in central Sri Lanka known as a key transit point on the Colombo–Kandy road and for its surrounding rubber and tea plantations.
  • B. Mirani
    Mirani is an electoral district in Queensland, Australia, represented in the state's Legislative Assembly.
  • C. Mirani
    Mirani is a small rural town and locality in Queensland, Australia, known for its sugarcane farming and proximity to the Pioneer Valley.
  • D. Madda
    Madda is a short form or nickname derived from the given name Maddalena.
  • E. Mokuola
    Mokuola is a small, lush island in Hilo Bay on Hawaii’s Big Island, known for its tranquil park, tidal pools, and scenic views of the bay and Mauna Kea.
  • 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: Madhoo
Triple: [Roja, starring, Madhoo]
Generated description
Madhoo is an Indian actress best known for her lead role in the critically acclaimed Tamil film "Roja" and her work across multiple Indian film industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Madhoo
Target entity description: Madhoo is an Indian actress best known for her lead role in the critically acclaimed Tamil film "Roja" and her work across multiple Indian film industries.
  • A. Mawanella
    Mawanella is a town in central Sri Lanka known as a key transit point on the Colombo–Kandy road and for its surrounding rubber and tea plantations.
  • B. Mirani
    Mirani is an electoral district in Queensland, Australia, represented in the state's Legislative Assembly.
  • C. Mirani
    Mirani is a small rural town and locality in Queensland, Australia, known for its sugarcane farming and proximity to the Pioneer Valley.
  • D. Madda
    Madda is a short form or nickname derived from the given name Maddalena.
  • E. Mokuola
    Mokuola is a small, lush island in Hilo Bay on Hawaii’s Big Island, known for its tranquil park, tidal pools, and scenic views of the bay and Mauna Kea.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9485dd88190bc2cf2adf39d48ee completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce894d82588190b558d5b2dc65eafe completed April 2, 2026, 3:20 p.m.
NEDg Description generation batch_69ce8a9ce1a08190a579f7f7a0319d01 completed April 2, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce8bdf1f148190ac832424661bd8e5 completed April 2, 2026, 3:31 p.m.
Created at: March 30, 2026, 6:20 p.m.