Triple

T8526763
Position Surface form Disambiguated ID Type / Status
Subject Southern District, Israel E201837 entity
Predicate containsCity P294 FINISHED
Object Netivot
Netivot is a growing city in southern Israel known for its diverse population, religious communities, and proximity to the Gaza Strip.
 E741851 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: Netivot | Statement: [Southern District, Israel, containsCity, Netivot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Netivot
Context triple: [Southern District, Israel, containsCity, Netivot]
  • A. Nirtzah
    Nirtzah is the concluding section of the Passover Haggadah, featuring songs, prayers, and expressions of hope for future redemption.
  • B. Netia
    Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
  • C. Netinera
    Netinera is a major private rail and bus transport company operating regional passenger services across Germany.
  • D. Netolicky
    Netolicky is the surname of Bob Netolicky, an American former professional basketball player known for his career in the American Basketball Association (ABA).
  • E. Noga
    Noga is a given name most notably borne by Israeli mathematician and computer scientist Noga Alon.
  • 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: Netivot
Triple: [Southern District, Israel, containsCity, Netivot]
Generated description
Netivot is a growing city in southern Israel known for its diverse population, religious communities, and proximity to the Gaza Strip.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Netivot
Target entity description: Netivot is a growing city in southern Israel known for its diverse population, religious communities, and proximity to the Gaza Strip.
  • A. Nirtzah
    Nirtzah is the concluding section of the Passover Haggadah, featuring songs, prayers, and expressions of hope for future redemption.
  • B. Netia
    Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
  • C. Netinera
    Netinera is a major private rail and bus transport company operating regional passenger services across Germany.
  • D. Netolicky
    Netolicky is the surname of Bob Netolicky, an American former professional basketball player known for his career in the American Basketball Association (ABA).
  • E. Noga
    Noga is a given name most notably borne by Israeli mathematician and computer scientist Noga Alon.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6477100819081fa20cb6b8ea3d7 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d49c1408190b7c23739409d1e3d completed April 2, 2026, 1:21 p.m.
NEDg Description generation batch_69ce6ee1bae4819099ef302138599b34 completed April 2, 2026, 1:28 p.m.
NED2 Entity disambiguation (via description) batch_69ce6fb93fd88190bc53a925473f9b71 completed April 2, 2026, 1:31 p.m.
Created at: March 30, 2026, 6:16 p.m.