Triple

T15541336
Position Surface form Disambiguated ID Type / Status
Subject Haim Levanon Street E370482 entity
Predicate namedAfter P63 FINISHED
Object Haim Levanon
Haim Levanon was an Israeli public figure and politician who served as mayor of Tel Aviv in the mid-20th century.
 E1163713 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: Haim Levanon | Statement: [Haim Levanon Street, namedAfter, Haim Levanon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haim Levanon
Context triple: [Haim Levanon Street, namedAfter, Haim Levanon]
  • A. Uri Sivan
    Uri Sivan is an Israeli physicist and academic leader known for his research in nanotechnology and for serving as president of the Technion – Israel Institute of Technology.
  • B. Dov Moran
    Dov Moran is an Israeli entrepreneur and inventor best known as the creator of the USB flash drive and a pioneer in the flash memory industry.
  • C. Ilan Eshkeri
    Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
  • D. Assaf Ramon
    Assaf Ramon was an Israeli Air Force fighter pilot and the son of astronaut Ilan Ramon, who died in a training accident in 2009.
  • E. Yishay Mansour
    Yishay Mansour is an Israeli computer scientist known for his contributions to algorithms, machine learning, and game theory, and for serving as a prominent professor at Tel Aviv University.
  • 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: Haim Levanon
Triple: [Haim Levanon Street, namedAfter, Haim Levanon]
Generated description
Haim Levanon was an Israeli public figure and politician who served as mayor of Tel Aviv in the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haim Levanon
Target entity description: Haim Levanon was an Israeli public figure and politician who served as mayor of Tel Aviv in the mid-20th century.
  • A. Uri Sivan
    Uri Sivan is an Israeli physicist and academic leader known for his research in nanotechnology and for serving as president of the Technion – Israel Institute of Technology.
  • B. Dov Moran
    Dov Moran is an Israeli entrepreneur and inventor best known as the creator of the USB flash drive and a pioneer in the flash memory industry.
  • C. Ilan Eshkeri
    Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
  • D. Assaf Ramon
    Assaf Ramon was an Israeli Air Force fighter pilot and the son of astronaut Ilan Ramon, who died in a training accident in 2009.
  • E. Yishay Mansour
    Yishay Mansour is an Israeli computer scientist known for his contributions to algorithms, machine learning, and game theory, and for serving as a prominent professor at Tel Aviv University.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04432c3808190bb5b653bf8de30c6 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4556ad008190a411ccd3ef0d1e89 completed May 9, 2026, 2:31 p.m.
NEDg Description generation batch_69ff47590f5c81908da35e6d85452eee completed May 9, 2026, 2:40 p.m.
NED2 Entity disambiguation (via description) batch_69ff47d81e408190888b86f3f69ca76e completed May 9, 2026, 2:42 p.m.
Created at: April 10, 2026, 4:07 a.m.