Triple

T7745694
Position Surface form Disambiguated ID Type / Status
Subject Alweg Monorail E175623 entity
Predicate manufacturer P490 FINISHED
Object Alweg E667056 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: Alweg | Statement: [Alweg Monorail, manufacturer, Alweg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alweg
Context triple: [Alweg Monorail, manufacturer, Alweg]
  • A. Alweg chosen
    Alweg was a pioneering German monorail company best known for developing the technology that inspired systems like the Disneyland Monorail and the Seattle Center Monorail.
  • B. Heemraadlaan
    Heemraadlaan is a metro station in Spijkenisse, Netherlands, serving as part of the Rotterdam Metro network.
  • C. Breedeweg
    Breedeweg is a village in the Dutch province of Gelderland, located within the municipality of Berg en Dal near the German border.
  • D. Blokzijl
    Blokzijl is a historic former trading town and harbor in the Dutch province of Overijssel, known for its picturesque canals and well-preserved old center.
  • E. Amsteg
    Amsteg is a village in the Swiss canton of Uri, situated in the Reuss Valley and known as a transport hub along the Gotthard route.
  • 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_69c69960b3588190a53aa590d31d9544 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7038b46bc8190b3a8a9da09d2b8df completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be4cdb148190af3ebaf9ac35b641 completed March 29, 2026, 5:53 a.m.
Created at: March 27, 2026, 4:07 p.m.