Triple

T13394078
Position Surface form Disambiguated ID Type / Status
Subject Quality E319652 entity
Predicate mainCharacter P1183 FINISHED
Object Gessler
Gessler is a fictional character best known as the tyrannical Austrian bailiff and antagonist in the William Tell legend.
E1039519 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: Gessler | Statement: [Quality, mainCharacter, Gessler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gessler
Context triple: [Quality, mainCharacter, Gessler]
  • A. Willy Hameister
    Willy Hameister was a German cinematographer best known for his influential work on early Expressionist cinema, including the landmark film "The Cabinet of Dr. Caligari."
  • B. Obertor
    Obertor is a historic city gate in Neuss, Germany, notable as one of the town’s best-preserved medieval fortification structures.
  • C. Albin Schelbert
    Albin Schelbert is a mountaineer known for being part of the team that made the first successful ascent of Dhaulagiri, one of the world’s highest peaks.
  • D. Werneck
    Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
  • E. Ottmar
    Ottmar is a German former football player and highly successful manager best known for leading Borussia Dortmund and Bayern Munich to numerous domestic and European titles.
  • 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: Gessler
Triple: [Quality, mainCharacter, Gessler]
Generated description
Gessler is a fictional character best known as the tyrannical Austrian bailiff and antagonist in the William Tell legend.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gessler
Target entity description: Gessler is a fictional character best known as the tyrannical Austrian bailiff and antagonist in the William Tell legend.
  • A. Willy Hameister
    Willy Hameister was a German cinematographer best known for his influential work on early Expressionist cinema, including the landmark film "The Cabinet of Dr. Caligari."
  • B. Obertor
    Obertor is a historic city gate in Neuss, Germany, notable as one of the town’s best-preserved medieval fortification structures.
  • C. Albin Schelbert
    Albin Schelbert is a mountaineer known for being part of the team that made the first successful ascent of Dhaulagiri, one of the world’s highest peaks.
  • D. Werneck
    Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
  • E. Ottmar
    Ottmar is a German former football player and highly successful manager best known for leading Borussia Dortmund and Bayern Munich to numerous domestic and European titles.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d74e5881909828854bba7d9a87 completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7306fb8348190a325a07a1ac858fd completed May 3, 2026, 11:24 a.m.
NEDg Description generation batch_69f731c912708190af0249952e8824fb completed May 3, 2026, 11:30 a.m.
NED2 Entity disambiguation (via description) batch_69f732c14f5c8190afd989200d250783 completed May 3, 2026, 11:34 a.m.
Created at: April 9, 2026, 9:34 p.m.