Triple

T2169740
Position Surface form Disambiguated ID Type / Status
Subject James Woods E48393 entity
Predicate notableWork P4 FINISHED
Object Diggstown
Diggstown is a 1992 sports comedy-drama film centered on a high-stakes boxing con set in a small Southern town.
 E241710 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: Diggstown | Statement: [James Woods, notableWork, Diggstown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Diggstown
Context triple: [James Woods, notableWork, Diggstown]
  • A. Shingletown
    Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
  • B. Milltown
    Milltown is a small hamlet within the Town of Southeast in Putnam County, New York.
  • C. Ambler
    Ambler is a small Inupiat community and city in northwestern Alaska, located along the Kobuk River above the Arctic Circle.
  • D. Peebles
    Peebles is a historic market town in the Scottish Borders, known for its scenic riverside setting, traditional architecture, and outdoor recreation.
  • E. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • 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: Diggstown
Triple: [James Woods, notableWork, Diggstown]
Generated description
Diggstown is a 1992 sports comedy-drama film centered on a high-stakes boxing con set in a small Southern town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Diggstown
Target entity description: Diggstown is a 1992 sports comedy-drama film centered on a high-stakes boxing con set in a small Southern town.
  • A. Shingletown
    Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
  • B. Milltown
    Milltown is a small hamlet within the Town of Southeast in Putnam County, New York.
  • C. Ambler
    Ambler is a small Inupiat community and city in northwestern Alaska, located along the Kobuk River above the Arctic Circle.
  • D. Peebles
    Peebles is a historic market town in the Scottish Borders, known for its scenic riverside setting, traditional architecture, and outdoor recreation.
  • E. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • 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_69a88aa3faa48190995b233af6525815 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbeaeb58881908ad34f7b253bac2a completed March 7, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d9a74e081909d8945fe03c8d0fa completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5e30a69c8190a3f77e784401f671 completed March 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae5ea4edcc81908829e4bd64ce0aea completed March 9, 2026, 5:46 a.m.
Created at: March 4, 2026, 7:45 p.m.