Triple

T5214712
Position Surface form Disambiguated ID Type / Status
Subject Walter Koenig E117722 entity
Predicate notableWork P4 FINISHED
Object Mad Cowgirl
Mad Cowgirl is a 2006 surreal, low-budget independent horror-thriller film known for its bizarre narrative and cult appeal.
 E503727 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: Mad Cowgirl | Statement: [Walter Koenig, notableWork, Mad Cowgirl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mad Cowgirl
Context triple: [Walter Koenig, notableWork, Mad Cowgirl]
  • A. Mad Cows
    Mad Cows is a 1999 British comedy film about a chaotic series of misadventures involving a young mother entangled in crime and bureaucracy.
  • B. Cowgirls
    The Cowgirls are the women's athletic teams representing the University of Wyoming in NCAA competition.
  • C. Cowgirls
    Cowgirls is the nickname for the women’s athletic teams representing Oklahoma State University in NCAA sports competitions.
  • D. The Cow
    The Cow is the English title of Surah Al-Baqarah, the Quran’s longest chapter, which covers core themes of faith, law, guidance, and the relationship between God and humanity.
  • E. Strolling of the Heifers
    Strolling of the Heifers is an annual agricultural-themed parade and festival in Brattleboro, Vermont, celebrating local farms, food, and rural life.
  • 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: Mad Cowgirl
Triple: [Walter Koenig, notableWork, Mad Cowgirl]
Generated description
Mad Cowgirl is a 2006 surreal, low-budget independent horror-thriller film known for its bizarre narrative and cult appeal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mad Cowgirl
Target entity description: Mad Cowgirl is a 2006 surreal, low-budget independent horror-thriller film known for its bizarre narrative and cult appeal.
  • A. Mad Cows
    Mad Cows is a 1999 British comedy film about a chaotic series of misadventures involving a young mother entangled in crime and bureaucracy.
  • B. Cowgirls
    The Cowgirls are the women's athletic teams representing the University of Wyoming in NCAA competition.
  • C. Cowgirls
    Cowgirls is the nickname for the women’s athletic teams representing Oklahoma State University in NCAA sports competitions.
  • D. The Cow
    The Cow is the English title of Surah Al-Baqarah, the Quran’s longest chapter, which covers core themes of faith, law, guidance, and the relationship between God and humanity.
  • E. Strolling of the Heifers
    Strolling of the Heifers is an annual agricultural-themed parade and festival in Brattleboro, Vermont, celebrating local farms, food, and rural life.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a928dfc8190971a9e28d5c10446 completed March 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefe325988190b35e3502f147c9c2 completed March 21, 2026, 7:22 p.m.
NEDg Description generation batch_69bef0b2b6448190be1c465738be741b completed March 21, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_69bef121817c8190aebd27ee34c0a419 completed March 21, 2026, 7:27 p.m.
Created at: March 20, 2026, 1:47 p.m.