Triple

T4023531
Position Surface form Disambiguated ID Type / Status
Subject Chaim Weizmann E91335 entity
Predicate placeOfBirth P1 FINISHED
Object Motal E97407 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: Motal | Statement: [Chaim Weizmann, placeOfBirth, Motal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Motal
Context triple: [Chaim Weizmann, placeOfBirth, Motal]
  • A. Motal chosen
    Motal is a small town in present-day Belarus, historically part of the Russian Empire, known as the birthplace of Israel’s first president, Chaim Weizmann.
  • B. Mota
    Mota is an Oceanic language of northern Vanuatu, historically notable as a regional lingua franca and early mission language in the area.
  • C. Maltoni
    Maltoni is the Italian maiden surname of Rosa Maltoni Mussolini, the mother of fascist dictator Benito Mussolini.
  • D. Mogilno
    Mogilno is a historic town in north-central Poland known for its medieval monastery and location in the Kuyavian-Pomeranian Voivodeship.
  • E. Mugatu
    Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
  • 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_69aed9618b04819081750d979d2af098 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeface7a788190a0e4e549a6816f91 completed March 9, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c82a33881908eb1b53331b10791 completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:35 p.m.