Triple

T10609869
Position Surface form Disambiguated ID Type / Status
Subject Raphael Mechoulam E275977 entity
Predicate notableStudent P4838 FINISHED
Object Lumír Hanuš
Lumír Hanuš is a Czech analytical chemist and cannabis researcher best known for co-discovering the endocannabinoid anandamide.
E876000 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: Lumír Hanuš | Statement: [Raphael Mechoulam, notableStudent, Lumír Hanuš]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lumír Hanuš
Context triple: [Raphael Mechoulam, notableStudent, Lumír Hanuš]
  • A. Jaromír Hanzlík
    Jaromír Hanzlík is a Czech film and television actor best known for his roles in popular Czechoslovak movies and TV series from the 1960s onward.
  • B. Jan Novák
    Jan Novák was a Czech composer known for his neoclassical style and film scores, including the music for the film "Atentát."
  • C. Jan Mareš
    Jan Mareš is a Czech academic who serves as the rector of Mendel University in Brno.
  • D. Aleš Hemský
    Aleš Hemský is a Czech former professional ice hockey right winger best known for his long NHL career with the Edmonton Oilers and his playmaking skill.
  • E. Ludvík Vaculík
    Ludvík Vaculík was a Czech writer, dissident, and influential critic of the communist regime, known for his samizdat essays and role in the Prague Spring and human rights movements.
  • 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: Lumír Hanuš
Triple: [Raphael Mechoulam, notableStudent, Lumír Hanuš]
Generated description
Lumír Hanuš is a Czech analytical chemist and cannabis researcher best known for co-discovering the endocannabinoid anandamide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lumír Hanuš
Target entity description: Lumír Hanuš is a Czech analytical chemist and cannabis researcher best known for co-discovering the endocannabinoid anandamide.
  • A. Jaromír Hanzlík
    Jaromír Hanzlík is a Czech film and television actor best known for his roles in popular Czechoslovak movies and TV series from the 1960s onward.
  • B. Jan Novák
    Jan Novák was a Czech composer known for his neoclassical style and film scores, including the music for the film "Atentát."
  • C. Jan Mareš
    Jan Mareš is a Czech academic who serves as the rector of Mendel University in Brno.
  • D. Aleš Hemský
    Aleš Hemský is a Czech former professional ice hockey right winger best known for his long NHL career with the Edmonton Oilers and his playmaking skill.
  • E. Ludvík Vaculík
    Ludvík Vaculík was a Czech writer, dissident, and influential critic of the communist regime, known for his samizdat essays and role in the Prague Spring and human rights movements.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df59468881909b0c67d3f08c4b76 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b716a088190b84982f1a8173e0a completed April 10, 2026, 9:28 p.m.
NEDg Description generation batch_69d96dee84f48190bf5b0cb1115a8bba completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d9708824208190acf75933962d690f completed April 10, 2026, 9:50 p.m.
Created at: April 8, 2026, 7:32 p.m.