Triple

T1247736
Position Surface form Disambiguated ID Type / Status
Subject Academy of the Hebrew Language E26804 entity
Predicate locatedIn P40 FINISHED
Object Givat Ram E163399 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: Givat Ram | Statement: [Academy of the Hebrew Language, locatedIn, Givat Ram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Givat Ram
Context triple: [Academy of the Hebrew Language, locatedIn, Givat Ram]
  • A. Givat Ram chosen
    Givat Ram is a central neighborhood and campus area in Jerusalem that hosts major national institutions, including the Knesset and the Hebrew University’s main campus.
  • B. Givatayim
    Givatayim is a small, densely populated city in Israel’s Tel Aviv metropolitan area, known for its residential character and proximity to major urban centers.
  • C. Rehovot
    Rehovot is a city in central Israel known for its scientific and agricultural research institutions, including the Weizmann Institute of Science.
  • D. Kiryat Ono
    Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
  • E. Herzliya
    Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
  • 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_69a49487a9c48190ba9b05348fd1b53f completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf6750a48190b86e9248ed54d90a completed March 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad231d1bdc8190bceaafcf86544bf1 completed March 8, 2026, 7:19 a.m.
Created at: March 1, 2026, 7:47 p.m.