Triple

T19543827
Position Surface form Disambiguated ID Type / Status
Subject Arthur Hailey E488983 entity
Predicate notableWork P4 FINISHED
Object Wheels
Wheels is a novel by Arthur Hailey that offers a dramatic, behind-the-scenes look at the American automobile industry and its corporate, political, and personal conflicts.
 E1381877 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: Wheels | Statement: [Arthur Hailey, notableWork, Wheels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wheels
Context triple: [Arthur Hailey, notableWork, Wheels]
  • A. Wheels
    "Wheels" is a country-rock song associated with musician Chris Hillman, reflecting his influential role in the development of the genre.
  • B. Wheels
    Wheels is a mathematical puzzle and recreational mathematics topic discussed in Martin Gardner’s collection "Wheels, Life and Other Mathematical Amusements."
  • C. Wheels
    "Wheels" is a song by Australian country singer-songwriter Kasey Chambers, recognized as one of her notable recordings.
  • D. Wheelie
    Wheelie is a small, wisecracking Autobot from the Transformers franchise known for his rhyming speech and comic-relief role.
  • E. Wheel 2000
    Wheel 2000 is a children-oriented adaptation of the game show "Wheel of Fortune," featuring kid contestants, simplified gameplay, and a futuristic, high-energy presentation.
  • 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: Wheels
Triple: [Arthur Hailey, notableWork, Wheels]
Generated description
Wheels is a novel by Arthur Hailey that offers a dramatic, behind-the-scenes look at the American automobile industry and its corporate, political, and personal conflicts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wheels
Target entity description: Wheels is a novel by Arthur Hailey that offers a dramatic, behind-the-scenes look at the American automobile industry and its corporate, political, and personal conflicts.
  • A. Wheels
    Wheels is a mathematical puzzle and recreational mathematics topic discussed in Martin Gardner’s collection "Wheels, Life and Other Mathematical Amusements."
  • B. Wheels
    "Wheels" is a song by Australian country singer-songwriter Kasey Chambers, recognized as one of her notable recordings.
  • C. Wheels
    "Wheels" is a country-rock song associated with musician Chris Hillman, reflecting his influential role in the development of the genre.
  • D. Wheelie
    Wheelie is a small, wisecracking Autobot from the Transformers franchise known for his rhyming speech and comic-relief role.
  • E. Wheel 2000
    Wheel 2000 is a children-oriented adaptation of the game show "Wheel of Fortune," featuring kid contestants, simplified gameplay, and a futuristic, high-energy presentation.
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e638750b288190aecdb0e18a1add62 completed April 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a074e84fcdc8190a1995f2981016361 completed May 15, 2026, 4:49 p.m.
NEDg Description generation batch_6a074f4f3c008190b6483a994b2309cd completed May 15, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_6a075019f0b48190ae2469b1979e6cce completed May 15, 2026, 4:55 p.m.
Created at: April 10, 2026, 1:41 p.m.