Triple

T11982765
Position Surface form Disambiguated ID Type / Status
Subject Disney Villains E285201 entity
Predicate includesCharacter P5716 FINISHED
Object Hans
Hans is the duplicitous prince and main human antagonist from Disney’s animated film "Frozen."
E75878 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: Hans | Statement: [Disney Villains, includesCharacter, Hans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans
Context triple: [Disney Villains, includesCharacter, Hans]
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • C. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • D. Oskar
    Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
  • E. Wolfgang
    Wolfgang is a recurring villain and boss character in the Skylanders video game series, known for his werewolf-like appearance and musical, sound-based attacks.
  • 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: Hans
Triple: [Disney Villains, includesCharacter, Hans]
Generated description
Hans is the duplicitous prince and main human antagonist from Disney’s animated film "Frozen."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hans
Target entity description: Hans is the duplicitous prince and main human antagonist from Disney’s animated film "Frozen."
  • A. Hans chosen
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • C. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • D. Oskar
    Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
  • E. Wolfgang
    Wolfgang is a recurring villain and boss character in the Skylanders video game series, known for his werewolf-like appearance and musical, sound-based attacks.
  • F. None of above.

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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903973c848190aac871d6dfecc74b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4721913108190bd767c671f6484de completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7c5af08190ab0bff1232530a0c completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47dd51e648190bddd41766221e22d completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.