Triple

T16685666
Position Surface form Disambiguated ID Type / Status
Subject Paresh Rawal E405455 entity
Predicate notableWork P4 FINISHED
Object Naam
Naam is a 1986 Hindi drama film, widely remembered for its emotional storyline and performances, particularly by actor Paresh Rawal.
E1227449 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: Naam | Statement: [Paresh Rawal, notableWork, Naam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naam
Context triple: [Paresh Rawal, notableWork, Naam]
  • A. Nama
    Nama is a Khoe language spoken primarily by the Nama people in Namibia and neighboring regions of southern Africa.
  • B. Nome
    Nome is a remote coastal city in western Alaska known historically for its gold rush heritage and as a key transportation and supply hub on the Bering Sea.
  • C. Nume
    Nume is an Oceanic language spoken on the island of Gaua in northern Vanuatu.
  • D. Nom
    Nom is a domain name marketplace and service platform operating under the brand Nom.com.
  • E. .name
    .name is a generic top-level domain (gTLD) primarily intended for personal websites and individual online identities.
  • 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: Naam
Triple: [Paresh Rawal, notableWork, Naam]
Generated description
Naam is a 1986 Hindi drama film, widely remembered for its emotional storyline and performances, particularly by actor Paresh Rawal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Naam
Target entity description: Naam is a 1986 Hindi drama film, widely remembered for its emotional storyline and performances, particularly by actor Paresh Rawal.
  • A. Nama
    Nama is a Khoe language spoken primarily by the Nama people in Namibia and neighboring regions of southern Africa.
  • B. Nome
    Nome is a remote coastal city in western Alaska known historically for its gold rush heritage and as a key transportation and supply hub on the Bering Sea.
  • C. Nume
    Nume is an Oceanic language spoken on the island of Gaua in northern Vanuatu.
  • D. Nom
    Nom is a domain name marketplace and service platform operating under the brand Nom.com.
  • E. .name
    .name is a generic top-level domain (gTLD) primarily intended for personal websites and individual online identities.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a43f6a08190913ca123a2377f95 completed May 10, 2026, 1:38 p.m.
NEDg Description generation batch_6a008b001c988190b0ddec3be0ed6fd0 completed May 10, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_6a008ba8227881908b1ac6e30d2e7c32 completed May 10, 2026, 1:44 p.m.
Created at: April 10, 2026, 5:19 a.m.