Triple

T13379292
Position Surface form Disambiguated ID Type / Status
Subject Mishmar HaGvul E319272 entity
Predicate shortName P43 FINISHED
Object Magav E319271 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: Magav | Statement: [Mishmar HaGvul, shortName, Magav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magav
Context triple: [Mishmar HaGvul, shortName, Magav]
  • A. Magav chosen
    Magav is the Hebrew name for Israel’s Border Police, a gendarmerie-style force responsible for border security, counterterrorism, and law enforcement in sensitive areas.
  • B. Magaw
    Magaw is a surname most notably associated with Robert Magaw, an American lawyer and Continental Army officer during the Revolutionary War.
  • C. Mahagi
    Mahagi is a town in northeastern Democratic Republic of the Congo, located near the border with Uganda in Ituri Province.
  • D. Mazani
    Mazani is an alternative name for the Mazanderani language, an Iranian language spoken primarily along the southern coast of the Caspian Sea in northern Iran.
  • E. Maho
    Maho is a town in Sri Lanka’s North Western Province known as a local commercial and transport hub in the Kurunegala District.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce56c6c8190adf4e19f6d1bc233 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f726893a8c8190b26b5f7c7fb96f1f completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:33 p.m.