Triple

T15614780
Position Surface form Disambiguated ID Type / Status
Subject Tante Ju E375383 entity
Predicate associatedWithManufacturerLocation P35004 FINISHED
Object Dessau E102721 NE FINISHED

How this triple was built (3 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: Dessau | Statement: [Tante Ju, associatedWithManufacturerLocation, Dessau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau
Context triple: [Tante Ju, associatedWithManufacturerLocation, Dessau]
  • A. Dessau chosen
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • B. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • C. Degendorf
    Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
  • D. Sangerhausen
    Sangerhausen is a town in the German state of Saxony-Anhalt, known for its historic mining heritage and its renowned Europa-Rosarium rose garden.
  • E. Riedenburg
    Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithManufacturerLocation
Context triple: [Tante Ju, associatedWithManufacturerLocation, Dessau]
  • A. manufacturerLocation chosen
    Indicates the geographic place where a product’s manufacturer is based or operates.
  • B. associatedWithLocality
    Indicates a relationship where something has a connection or relevance to a specific geographic place or locality.
  • C. associatedWithTeamLocation
    Indicates that an entity has a relationship or connection to the geographic location of a specific team.
  • D. isAssociatedWith
    Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
  • E. usedByManufacturer
    Indicates that a manufacturer makes use of a particular resource, component, method, or tool in its production or operational processes.
  • F. None of above.

Provenance (4 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e83407c8190abbcd4b7fab0ff85 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002d966ffc8190aa0d9d3abf8ad593 completed May 10, 2026, 7:02 a.m.
PD Predicate disambiguation batch_69deda844af081909e658ebc9d9b403d completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:13 a.m.