Triple

T7036604
Position Surface form Disambiguated ID Type / Status
Subject Givat Ram E163399 entity
Predicate languageOfToponym P15 FINISHED
Object Hebrew LITERAL FINISHED

How this triple was built (1 step)

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: Hebrew | Statement: [Givat Ram, languageOfToponym, Hebrew]

Provenance (2 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_69c6885e7c1c8190be32a8f79ab4e0cf completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e221a7988190b6b69782a275abb7 completed March 27, 2026, 8:01 p.m.
Created at: March 27, 2026, 2:36 p.m.