Triple

T22474537
Position Surface form Disambiguated ID Type / Status
Subject Sharon Subdistrict E555592 entity
Predicate contains P35 FINISHED
Object Kadima-Zoran
Kadima-Zoran is a local council in central Israel known for its residential communities and location within the Sharon region.
E1538582 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: Kadima-Zoran | Statement: [Sharon Subdistrict, contains, Kadima-Zoran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kadima-Zoran
Context triple: [Sharon Subdistrict, contains, Kadima-Zoran]
  • A. Zoran
    Zoran is a masculine given name commonly used in several Slavic countries, particularly in the Balkans.
  • B. Ramush
    Ramush is a Kosovar politician and former guerrilla commander who has served as Prime Minister of Kosovo.
  • C. Zoran Korach
    Zoran Korach is an American actor best known for his comedic television roles, including recurring parts on Nickelodeon and other network series.
  • D. Gligorov
    Gligorov is a South Slavic surname most prominently associated with Kiro Gligorov, the first President of independent Macedonia.
  • E. Zoran Krneta
    Zoran Krneta is a football executive best known as the inaugural sporting leader and roster architect for Major League Soccer expansion club Charlotte FC.
  • 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: Kadima-Zoran
Triple: [Sharon Subdistrict, contains, Kadima-Zoran]
Generated description
Kadima-Zoran is a local council in central Israel known for its residential communities and location within the Sharon region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kadima-Zoran
Target entity description: Kadima-Zoran is a local council in central Israel known for its residential communities and location within the Sharon region.
  • A. Zoran
    Zoran is a masculine given name commonly used in several Slavic countries, particularly in the Balkans.
  • B. Ramush
    Ramush is a Kosovar politician and former guerrilla commander who has served as Prime Minister of Kosovo.
  • C. Zoran Korach
    Zoran Korach is an American actor best known for his comedic television roles, including recurring parts on Nickelodeon and other network series.
  • D. Gligorov
    Gligorov is a South Slavic surname most prominently associated with Kiro Gligorov, the first President of independent Macedonia.
  • E. Zoran Krneta
    Zoran Krneta is a football executive best known as the inaugural sporting leader and roster architect for Major League Soccer expansion club Charlotte FC.
  • 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_69e11e52c2048190952dc5df209b9bed completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15be2d5388190a59d11b3403d998b completed April 29, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b125dda888190a266454969014eb7 completed May 18, 2026, 1:21 p.m.
NEDg Description generation batch_6a0b1388d8a481908d61f578fde9991d completed May 18, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_6a0b1462413c819086c2de0e62b2648a completed May 18, 2026, 1:30 p.m.
Created at: April 16, 2026, 8:49 p.m.