Triple

T552916
Position Surface form Disambiguated ID Type / Status
Subject Zdeno Chára E11879 entity
Predicate playedFor P2170 FINISHED
Object HC Lev Praha
HC Lev Praha was a professional ice hockey club based in Prague, Czech Republic, that competed in the Kontinental Hockey League (KHL).
E69322 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: HC Lev Praha | Statement: [Zdeno Chára, playedFor, HC Lev Praha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HC Lev Praha
Context triple: [Zdeno Chára, playedFor, HC Lev Praha]
  • A. HIFK Helsinki
    HIFK Helsinki is a prominent professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and traditional teams in the Liiga.
  • B. CSKA Moscow
    CSKA Moscow is a major Russian sports club best known for its successful football and basketball teams and intense rivalries with other Moscow clubs.
  • C. Jokerit
    Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
  • D. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • E. Dynamo Moscow
    Dynamo Moscow is a prominent Russian professional ice hockey club based in Moscow, historically known for developing elite players such as Alex Ovechkin.
  • 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: HC Lev Praha
Triple: [Zdeno Chára, playedFor, HC Lev Praha]
Generated description
HC Lev Praha was a professional ice hockey club based in Prague, Czech Republic, that competed in the Kontinental Hockey League (KHL).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: HC Lev Praha
Target entity description: HC Lev Praha was a professional ice hockey club based in Prague, Czech Republic, that competed in the Kontinental Hockey League (KHL).
  • A. HIFK Helsinki
    HIFK Helsinki is a prominent professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and traditional teams in the Liiga.
  • B. CSKA Moscow
    CSKA Moscow is a major Russian sports club best known for its successful football and basketball teams and intense rivalries with other Moscow clubs.
  • C. Jokerit
    Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
  • D. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • E. Dynamo Moscow
    Dynamo Moscow is a prominent Russian professional ice hockey club based in Moscow, historically known for developing elite players such as Alex Ovechkin.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4991b296481908cf27e1d1ec67052 completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e3f90058819081167bac387f8023 completed March 2, 2026, 1:12 a.m.
NEDg Description generation batch_69a4e497da648190b9e07fe94488be0d completed March 2, 2026, 1:15 a.m.
NED2 Entity disambiguation (via description) batch_69a4e525eb18819083018d392ba4b2fa completed March 2, 2026, 1:17 a.m.
Created at: March 1, 2026, 7:32 p.m.