Triple

T8686578
Position Surface form Disambiguated ID Type / Status
Subject Bender E206173 entity
Predicate hasAlternativeName P39 FINISHED
Object Tighina E555729 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: Tighina | Statement: [Bender, hasAlternativeName, Tighina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tighina
Context triple: [Bender, hasAlternativeName, Tighina]
  • A. Tighina chosen
    Tighina is a historic city in present-day Moldova, also known as Bender, which has long held strategic importance on the Dniester River.
  • B. Târgoviște
    Târgoviște is a historic city in southern Romania, known as a former Wallachian capital and the site where Nicolae Ceaușescu was executed in 1989.
  • C. Sinaia
    Sinaia is a Romanian mountain resort town in the Carpathians, famed for Peleș Castle and its historic role as a royal summer residence.
  • D. Tecuci
    Tecuci is a town in eastern Romania known as a local transport hub and administrative center in Galați County.
  • E. Tarom
    Tarom is Romania's national flag carrier airline, operating domestic and international flights primarily from its hub in Bucharest.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5730309081909a9a0256c9bf5f8f completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69d09b22da4c81909aacc9c4a6af379c completed April 4, 2026, 5:01 a.m.
Created at: March 30, 2026, 6:33 p.m.