Triple

T9356583
Position Surface form Disambiguated ID Type / Status
Subject The 158-Pound Marriage E225154 entity
Predicate hasCharacter P2308 FINISHED
Object Uta
Uta is a central character in John Irving’s novel "The 158-Pound Marriage," depicted as a complex, emotionally conflicted woman involved in an experimental partner-swapping arrangement.
 E794115 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: Uta | Statement: [The 158-Pound Marriage, hasCharacter, Uta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Uta
Context triple: [The 158-Pound Marriage, hasCharacter, Uta]
  • A. Hatohobei
    Hatohobei is a small, remote coral island state of Palau in the western Pacific Ocean, also known as Tobi.
  • B. Ukiha
    Ukiha is a small city in southwestern Japan known for its rural landscapes, fruit orchards, and traditional townscapes.
  • C. Suwawa
    Suwawa is an Austronesian language spoken by the Suwawa people in the northern part of Sulawesi, Indonesia.
  • D. Shumshu
    Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
  • E. Yoiyama
    Yoiyama is the lively evening street festival held before the main Gion Matsuri parade in Kyoto, featuring illuminated festival floats, food stalls, and traditional music.
  • 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: Uta
Triple: [The 158-Pound Marriage, hasCharacter, Uta]
Generated description
Uta is a central character in John Irving’s novel "The 158-Pound Marriage," depicted as a complex, emotionally conflicted woman involved in an experimental partner-swapping arrangement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Uta
Target entity description: Uta is a central character in John Irving’s novel "The 158-Pound Marriage," depicted as a complex, emotionally conflicted woman involved in an experimental partner-swapping arrangement.
  • A. Hatohobei
    Hatohobei is a small, remote coral island state of Palau in the western Pacific Ocean, also known as Tobi.
  • B. Ukiha
    Ukiha is a small city in southwestern Japan known for its rural landscapes, fruit orchards, and traditional townscapes.
  • C. Suwawa
    Suwawa is an Austronesian language spoken by the Suwawa people in the northern part of Sulawesi, Indonesia.
  • D. Shumshu
    Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
  • E. Yoiyama
    Yoiyama is the lively evening street festival held before the main Gion Matsuri parade in Kyoto, featuring illuminated festival floats, food stalls, and traditional music.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4fee9d4c8190a7d121c9487ccca2 completed April 1, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3d248a88190b7d17af66e2903c5 completed April 4, 2026, 11:19 a.m.
NEDg Description generation batch_69d0f46bd034819093e7157a3e1ac1fc completed April 4, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_69d0f5bf64548190b40e97b279db5105 completed April 4, 2026, 11:27 a.m.
Created at: March 30, 2026, 7:42 p.m.