Triple

T17098288
Position Surface form Disambiguated ID Type / Status
Subject Bhupinder Singh Hooda E414906 entity
Predicate familyName P18 FINISHED
Object Hooda
Hooda is an Indian surname commonly associated with prominent political and public figures, particularly in the state of Haryana.
 E1249751 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: Hooda | Statement: [Bhupinder Singh Hooda, familyName, Hooda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hooda
Context triple: [Bhupinder Singh Hooda, familyName, Hooda]
  • A. Pluzz
    Pluzz was France Télévisions’ former online catch-up TV and streaming platform, later succeeded by france.tv.
  • B. Simogo
    Simogo is an independent Swedish game development studio known for its stylish, narrative-driven titles that blend music, art, and innovative gameplay.
  • C. Pengo
    Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
  • D. Gadzoom
    Gadzoom is a high-speed chairlift at Snowbird Ski and Summer Resort in Utah, serving popular intermediate and advanced terrain.
  • E. Hacko
    Hacko is the nickname of Lorenz Hackenholt, an SS officer who played a key role in operating gas chambers during the Holocaust.
  • 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: Hooda
Triple: [Bhupinder Singh Hooda, familyName, Hooda]
Generated description
Hooda is an Indian surname commonly associated with prominent political and public figures, particularly in the state of Haryana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hooda
Target entity description: Hooda is an Indian surname commonly associated with prominent political and public figures, particularly in the state of Haryana.
  • A. Pluzz
    Pluzz was France Télévisions’ former online catch-up TV and streaming platform, later succeeded by france.tv.
  • B. Simogo
    Simogo is an independent Swedish game development studio known for its stylish, narrative-driven titles that blend music, art, and innovative gameplay.
  • C. Pengo
    Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
  • D. Gadzoom
    Gadzoom is a high-speed chairlift at Snowbird Ski and Summer Resort in Utah, serving popular intermediate and advanced terrain.
  • E. Hacko
    Hacko is the nickname of Lorenz Hackenholt, an SS officer who played a key role in operating gas chambers during the Holocaust.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbffafb08190baf9e0b4fdf1b404 completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012eefd5f08190b9eb8a81e45a9921 completed May 11, 2026, 1:20 a.m.
NEDg Description generation batch_6a012fe2a1b081909483baef845cc2c1 completed May 11, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a0130c2ad9881909d8a8b64ebb59aa6 completed May 11, 2026, 1:28 a.m.
Created at: April 10, 2026, 5:35 a.m.