Triple

T18671026
Position Surface form Disambiguated ID Type / Status
Subject Schichau-Werke E456474 entity
Predicate headquartersLocation P62 FINISHED
Object Elbing 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: Elbing | Statement: [Schichau-Werke, headquartersLocation, Elbing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elbing
Context triple: [Schichau-Werke, headquartersLocation, Elbing]
  • A. 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.
  • B. Jachenau
    Jachenau is a small Bavarian municipality in southern Germany, known for its scenic alpine landscape and traditional rural character.
  • C. Slutsk
    Slutsk is a historic town in central Belarus known for its role as a regional center and for its traditional Slutsk belts.
  • D. Babruysk
    Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
  • E. Bromberg
    Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
  • 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_69d8d38f72b4819090a935175d9ca8af completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e556b21d2481908e1b8b583bfabb72 completed April 19, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05234f9ff0819080edb5ed9e4ffcc6 completed May 14, 2026, 1:20 a.m.
Created at: April 10, 2026, 11:48 a.m.