Triple

T14823485
Position Surface form Disambiguated ID Type / Status
Subject Michael I of Romania E348512 entity
Predicate placeOfBirth P1 FINISHED
Object Sinaia E451203 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: Sinaia | Statement: [Michael I of Romania, placeOfBirth, Sinaia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinaia
Context triple: [Michael I of Romania, placeOfBirth, Sinaia]
  • A. Sinaia chosen
    Sinaia is a Romanian mountain resort town in the Carpathians, famed for Peleș Castle and its historic role as a royal summer residence.
  • B. Tighina
    Tighina is a historic city in present-day Moldova, also known as Bender, which has long held strategic importance on the Dniester River.
  • C. Baia Mare
    Baia Mare is a city in northwestern Romania known for its mining history, surrounding Carpathian landscapes, and role as an important regional cultural and economic center.
  • D. Tecuci
    Tecuci is a town in eastern Romania known as a local transport hub and administrative center in Galați County.
  • E. Soroca
    Soroca is a historic town in northern Moldova known for its well-preserved medieval fortress on the banks of the Dniester River.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe7a8dc8190bcb5ecfa1cbf1601 completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c78f36d88190a39f407c5d8dbc0d completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 1:51 a.m.