Triple

T8573408
Position Surface form Disambiguated ID Type / Status
Subject Haason Reddick E202984 entity
Predicate givenName P17 FINISHED
Object Haason
Haason is the given name of American football linebacker Haason Reddick, known for his pass-rushing ability in the NFL.
 E742539 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: Haason | Statement: [Haason Reddick, givenName, Haason]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haason
Context triple: [Haason Reddick, givenName, Haason]
  • A. Haro
    Haro is a historic town in Spain’s La Rioja region, renowned for its wineries and annual wine festival.
  • B. Haisyn
    Haisyn is a city in central Ukraine known as a local administrative and economic center within Vinnytsia Oblast.
  • C. Hundon
    Hundon is a rural village and civil parish located in the English county of Suffolk.
  • D. Norriss
    Norriss is a variant spelling of the surname Norris, which is of English origin and historically associated with the meaning "northerner" or "from the north."
  • E. Hase
    The Hase is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia, passing towns such as Quakenbrück before joining the Ems.
  • 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: Haason
Triple: [Haason Reddick, givenName, Haason]
Generated description
Haason is the given name of American football linebacker Haason Reddick, known for his pass-rushing ability in the NFL.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haason
Target entity description: Haason is the given name of American football linebacker Haason Reddick, known for his pass-rushing ability in the NFL.
  • A. Haro
    Haro is a historic town in Spain’s La Rioja region, renowned for its wineries and annual wine festival.
  • B. Haisyn
    Haisyn is a city in central Ukraine known as a local administrative and economic center within Vinnytsia Oblast.
  • C. Hundon
    Hundon is a rural village and civil parish located in the English county of Suffolk.
  • D. Norriss
    Norriss is a variant spelling of the surname Norris, which is of English origin and historically associated with the meaning "northerner" or "from the north."
  • E. Hase
    The Hase is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia, passing towns such as Quakenbrück before joining the Ems.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea458c1081908e79bee2cbf97207 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce898cf8648190b52758b6ecf2959b completed April 2, 2026, 3:21 p.m.
NEDg Description generation batch_69ce8a9df47c81909ba9ef8dff1db7b1 completed April 2, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce8b48841c8190bcf11aeb25355649 completed April 2, 2026, 3:29 p.m.
Created at: March 30, 2026, 6:21 p.m.