Triple

T3939064
Position Surface form Disambiguated ID Type / Status
Subject Czech koruna E91987 entity
Predicate subunit P35 FINISHED
Object haléř
Haléř was a former fractional monetary unit of the Czech Republic, equal to one hundredth of a Czech koruna.
 E399937 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: haléř | Statement: [Czech koruna, subunit, haléř]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: haléř
Context triple: [Czech koruna, subunit, haléř]
  • A. Halaby
    Halaby is the maiden surname of Queen Noor of Jordan, reflecting her Syrian-American family heritage.
  • B. Úhlava
    Úhlava is a river in the Czech Republic that flows through the city of Plzeň and is one of the region’s notable waterways.
  • C. Heissler
    Heissler is a German-language surname most notably associated with the animated character Klaus Heissler from the television series "American Dad!".
  • D. Helleren
    Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
  • E. Tále
    Tále is a popular ski resort and recreational area in the Low Tatras mountains of central Slovakia, known for its slopes, golf course, and year-round outdoor activities.
  • 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: haléř
Triple: [Czech koruna, subunit, haléř]
Generated description
Haléř was a former fractional monetary unit of the Czech Republic, equal to one hundredth of a Czech koruna.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: haléř
Target entity description: Haléř was a former fractional monetary unit of the Czech Republic, equal to one hundredth of a Czech koruna.
  • A. Halaby
    Halaby is the maiden surname of Queen Noor of Jordan, reflecting her Syrian-American family heritage.
  • B. Úhlava
    Úhlava is a river in the Czech Republic that flows through the city of Plzeň and is one of the region’s notable waterways.
  • C. Heissler
    Heissler is a German-language surname most notably associated with the animated character Klaus Heissler from the television series "American Dad!".
  • D. Helleren
    Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
  • E. Tále
    Tále is a popular ski resort and recreational area in the Low Tatras mountains of central Slovakia, known for its slopes, golf course, and year-round outdoor activities.
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedfb12b88190a6ca6574b1aadb6e completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b528922a548190a8e5339deacaefd9 completed March 14, 2026, 9:21 a.m.
NEDg Description generation batch_69b5298e517c819085c1dcb943a4d8a2 completed March 14, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69b52a9b96ec8190812d846de6f061b6 completed March 14, 2026, 9:30 a.m.
Created at: March 9, 2026, 3:24 p.m.