Triple

T9401805
Position Surface form Disambiguated ID Type / Status
Subject Elbing E226489 entity
Predicate historicalName P65 FINISHED
Object Elbinga E226489 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: Elbinga | Statement: [Elbing, historicalName, Elbinga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elbinga
Context triple: [Elbing, historicalName, Elbinga]
  • A. Bellenberg
    Bellenberg is a small municipality in the Bavarian region of Swabia in southern Germany.
  • B. Mochau
    Mochau is a small locality in the German state of Saxony, situated within the administrative district of Mittelsachsen.
  • C. Elbing chosen
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • D. Löwenberg
    Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
  • E. Bogrod
    Bogrod is a goblin banker who works at Gringotts Wizarding Bank in the Harry Potter series.
  • 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_69ca843170f88190800a8ab2b5fc568e completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51be35cc8190bafad423a142c305 completed April 1, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1079798048190a1bd5318df4b1649 completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:46 p.m.