Triple

T29945073
Position Surface form Disambiguated ID Type / Status
Subject Bohuslav E760607 entity
Predicate hasNotableBearer P458 FINISHED
Object Bohuslav Ebermann
Bohuslav Ebermann is a former Czech ice hockey forward who played for the Czechoslovak national team, winning multiple World Championship medals and an Olympic silver in the 1970s.
E1944777 NE FINISHED

How this triple was built (2 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: Bohuslav Ebermann | Statement: [Bohuslav, hasNotableBearer, Bohuslav Ebermann]
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: Bohuslav Ebermann
Triple: [Bohuslav, hasNotableBearer, Bohuslav Ebermann]
Generated description
Bohuslav Ebermann is a former Czech ice hockey forward who played for the Czechoslovak national team, winning multiple World Championship medals and an Olympic silver in the 1970s.

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_69f22463f3648190a603c3ff305c660b completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6780b3dfc8190b47ef5d8a0cfccc8 completed May 2, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292aead9b88190b1c81dbd68981094 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292c3e3b208190b586c78f19a0fb49 completed June 10, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a292dc95bb8819088c869319844df08 completed June 10, 2026, 9:26 a.m.
Created at: April 29, 2026, 6:23 p.m.