Triple

T10285197
Position Surface form Disambiguated ID Type / Status
Subject The Strange Love of Martha Ivers E241208 entity
Predicate narrativeLocation P40 FINISHED
Object Iverstown
Iverstown is the fictional, gloomy industrial town that serves as the central setting in the film noir drama "The Strange Love of Martha Ivers."
E852659 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: Iverstown | Statement: [The Strange Love of Martha Ivers, narrativeLocation, Iverstown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iverstown
Context triple: [The Strange Love of Martha Ivers, narrativeLocation, Iverstown]
  • A. Stewartstown
    Stewartstown is a small village in County Tyrone, Northern Ireland, known for its rural character and historic market-town origins.
  • B. Shingletown
    Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
  • C. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • D. Culvertown
    Culvertown is a small unincorporated community located in Nelson County, Kentucky, known for its rural character and historic Catholic roots.
  • E. Longaville
    Longaville is one of the three lords attending King Navarre in Shakespeare’s comedy *Love’s Labour’s Lost*, known for his vow of scholarly abstinence that is soon undermined by love.
  • 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: Iverstown
Triple: [The Strange Love of Martha Ivers, narrativeLocation, Iverstown]
Generated description
Iverstown is the fictional, gloomy industrial town that serves as the central setting in the film noir drama "The Strange Love of Martha Ivers."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Iverstown
Target entity description: Iverstown is the fictional, gloomy industrial town that serves as the central setting in the film noir drama "The Strange Love of Martha Ivers."
  • A. Stewartstown
    Stewartstown is a small village in County Tyrone, Northern Ireland, known for its rural character and historic market-town origins.
  • B. Shingletown
    Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
  • C. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • D. Culvertown
    Culvertown is a small unincorporated community located in Nelson County, Kentucky, known for its rural character and historic Catholic roots.
  • E. Longaville
    Longaville is one of the three lords attending King Navarre in Shakespeare’s comedy *Love’s Labour’s Lost*, known for his vow of scholarly abstinence that is soon undermined by love.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2b737788190bfadd0d48ad38f5b completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8444c48819095100c6d1d45ccc7 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcae243c819095a2e791716805bd completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd3495fc8190a093d2536cfbe58a completed April 9, 2026, 1:13 a.m.
Created at: April 6, 2026, 11:40 a.m.