Triple

T15658030
Position Surface form Disambiguated ID Type / Status
Subject Ganei Tikva E376495 entity
Predicate locatedNear P294 FINISHED
Object Kiryat Ono E158565 NE FINISHED

How this triple was built (2 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: Kiryat Ono | Statement: [Ganei Tikva, locatedNear, Kiryat Ono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiryat Ono
Context triple: [Ganei Tikva, locatedNear, Kiryat Ono]
  • A. Kiryat Ono chosen
    Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
  • B. Kiryat Haim
    Kiryat Haim is a coastal neighborhood in the northern Israeli city of Haifa, known for its beachfront, residential character, and proximity to the Haifa Bay industrial and port areas.
  • C. Kiryat Shmona
    Kiryat Shmona is a northern Israeli city near the Lebanese border, known for its strategic location and frequent exposure to cross-border conflict.
  • D. Kiryat Gat
    Kiryat Gat is a city in south-central Israel known for its industrial zones, high-tech facilities, and location between the coastal plain and the Negev desert.
  • E. Kfar Saba
    Kfar Saba is a city in central Israel, known as a suburban and commercial hub in the Sharon plain near Tel Aviv.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ef3cb8c8190a10815b675b341c1 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a009d232074819083f58de3ee5fbf7d completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 4:15 a.m.