Triple

T5965726
Position Surface form Disambiguated ID Type / Status
Subject Haifa District E132745 entity
Predicate containsCity P294 FINISHED
Object Umm al-Fahm
Umm al-Fahm is a major Arab city in northern Israel known for its predominantly Palestinian population and significant cultural and political influence.
E580792 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: Umm al-Fahm | Statement: [Haifa District, containsCity, Umm al-Fahm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umm al-Fahm
Context triple: [Haifa District, containsCity, Umm al-Fahm]
  • A. Nahariya
    Nahariya is a coastal city in northern Israel on the Mediterranean Sea, known as a resort town and gateway to nearby attractions such as Rosh HaNikra.
  • B. Kfar Shmaryahu
    Kfar Shmaryahu is an affluent suburban village in central Israel known for its high standard of living and proximity to Tel Aviv.
  • C. Isfiya
    Isfiya is a Druze-majority village and local council located on Mount Carmel in northern Israel.
  • D. Kfar Saba
    Kfar Saba is a city in central Israel, known as a suburban and commercial hub in the Sharon plain near Tel Aviv.
  • E. Ma'alot-Tarshiha
    Ma'alot-Tarshiha is a mixed Jewish-Arab city in northern Israel known for its scenic Galilean setting and combined development-town and historic village character.
  • 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: Umm al-Fahm
Triple: [Haifa District, containsCity, Umm al-Fahm]
Generated description
Umm al-Fahm is a major Arab city in northern Israel known for its predominantly Palestinian population and significant cultural and political influence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Umm al-Fahm
Target entity description: Umm al-Fahm is a major Arab city in northern Israel known for its predominantly Palestinian population and significant cultural and political influence.
  • A. Nahariya
    Nahariya is a coastal city in northern Israel on the Mediterranean Sea, known as a resort town and gateway to nearby attractions such as Rosh HaNikra.
  • B. Kfar Shmaryahu
    Kfar Shmaryahu is an affluent suburban village in central Israel known for its high standard of living and proximity to Tel Aviv.
  • C. Isfiya
    Isfiya is a Druze-majority village and local council located on Mount Carmel in northern Israel.
  • D. Kfar Saba
    Kfar Saba is a city in central Israel, known as a suburban and commercial hub in the Sharon plain near Tel Aviv.
  • E. Ma'alot-Tarshiha
    Ma'alot-Tarshiha is a mixed Jewish-Arab city in northern Israel known for its scenic Galilean setting and combined development-town and historic village character.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3ca1dc819098cde8ae5ec1d845 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c2439f6cc08190bb7a4c6a0b7727c6 completed March 24, 2026, 7:56 a.m.
NEDg Description generation batch_69c4fb66b8e8819090524d1ef12688a7 completed March 26, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_69c4fc3065bc81908d95fbd3d4655c76 completed March 26, 2026, 9:28 a.m.
Created at: March 22, 2026, 4:03 p.m.