Triple

T4770985
Position Surface form Disambiguated ID Type / Status
Subject Leon Pinsker E105925 entity
Predicate placeOfBirth P1 FINISHED
Object Tomaszów Lubelski E479235 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: Tomaszów Lubelski | Statement: [Leon Pinsker, placeOfBirth, Tomaszów Lubelski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomaszów Lubelski
Context triple: [Leon Pinsker, placeOfBirth, Tomaszów Lubelski]
  • A. Tomaszów Lubelski chosen
    Tomaszów Lubelski is a town in eastern Poland known for its historical wooden architecture and location near the Roztocze National Park.
  • B. Ostrołęka
    Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and as a local industrial and administrative center.
  • C. Mielec
    Mielec is a town in southeastern Poland known for its aviation industry and manufacturing sector.
  • D. Bolesławiec
    Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
  • E. Łowicz
    Łowicz is a historic town in central Poland known for its rich folk traditions, distinctive regional costumes, and baroque architecture.
  • 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_69bd43f226fc8190b867cc249c2a9042 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd655e5dcc8190a932be9b1baaffb2 completed March 20, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5187dfe008190ac60e042527e55b3 completed March 26, 2026, 11:29 a.m.
Created at: March 20, 2026, 1:21 p.m.