Triple

T2139814
Position Surface form Disambiguated ID Type / Status
Subject Toy Story 2 E46735 entity
Predicate mainCharacter P1183 FINISHED
Object Hamm
Hamm is the wisecracking plastic piggy bank toy from the Toy Story film series, known for his sarcastic humor and loyalty to Andy’s other toys.
 E237533 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: Hamm | Statement: [Toy Story 2, mainCharacter, Hamm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hamm
Context triple: [Toy Story 2, mainCharacter, Hamm]
  • A. Hamm
    Hamm is a city in North Rhine-Westphalia, Germany, known for its industrial heritage and strategic location in the Ruhr region.
  • B. Hammann
    Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
  • C. Hamura
    Hamura is a city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama River.
  • D. Galli
    Galli is the Latin term for the ancient Celtic peoples of Gaul, roughly corresponding to modern-day France and surrounding regions.
  • E. Johanus
    Johanus is a given name, likely a variant or diminutive of Johan, used as a personal first name in some cultures.
  • 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: Hamm
Triple: [Toy Story 2, mainCharacter, Hamm]
Generated description
Hamm is the wisecracking plastic piggy bank toy from the Toy Story film series, known for his sarcastic humor and loyalty to Andy’s other toys.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hamm
Target entity description: Hamm is the wisecracking plastic piggy bank toy from the Toy Story film series, known for his sarcastic humor and loyalty to Andy’s other toys.
  • A. Hamm
    Hamm is a city in North Rhine-Westphalia, Germany, known for its industrial heritage and strategic location in the Ruhr region.
  • B. Hammann
    Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
  • C. Hamura
    Hamura is a city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama River.
  • D. Galli
    Galli is the Latin term for the ancient Celtic peoples of Gaul, roughly corresponding to modern-day France and surrounding regions.
  • E. Johanus
    Johanus is a given name, likely a variant or diminutive of Johan, used as a personal first name in some cultures.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe025d3c81908bcb33a7ff09eae8 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b37ce08190add9df46cc17ba89 completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae52e539f081908424c4093c125861 completed March 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae5357e1088190bcffccb37030f3fc completed March 9, 2026, 4:58 a.m.
Created at: March 4, 2026, 7:44 p.m.