Triple

T2210263
Position Surface form Disambiguated ID Type / Status
Subject Jim Hanifan E50899 entity
Predicate familyName P18 FINISHED
Object Hanifan
Hanifan is a surname most notably associated with Jim Hanifan, an American football coach and former player.
 E245570 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: Hanifan | Statement: [Jim Hanifan, familyName, Hanifan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hanifan
Context triple: [Jim Hanifan, familyName, Hanifan]
  • A. Hani
    The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
  • B. Afif
    Afif is a town in central Saudi Arabia known as an inland community within the Riyadh administrative region.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • E. Honancho
    Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
  • 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: Hanifan
Triple: [Jim Hanifan, familyName, Hanifan]
Generated description
Hanifan is a surname most notably associated with Jim Hanifan, an American football coach and former player.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hanifan
Target entity description: Hanifan is a surname most notably associated with Jim Hanifan, an American football coach and former player.
  • A. Hani
    The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
  • B. Afif
    Afif is a town in central Saudi Arabia known as an inland community within the Riyadh administrative region.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • E. Honancho
    Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfce5abc8190b90b92e32045385d completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae655045d081909b8294ec706e0814 completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae662f689881908ecd76952b78f863 completed March 9, 2026, 6:18 a.m.
NED2 Entity disambiguation (via description) batch_69ae668ef8bc819085ed1c83f447d396 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:46 p.m.