Triple

T15913562
Position Surface form Disambiguated ID Type / Status
Subject Salzwedel E385908 entity
Predicate locatedIn P40 FINISHED
Object Altmark E650810 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: Altmark | Statement: [Salzwedel, locatedIn, Altmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altmark
Context triple: [Salzwedel, locatedIn, Altmark]
  • A. Altmark
    Altmark was a German naval auxiliary ship best known for its role in the early World War II "Altmark Incident," when British forces freed prisoners being held aboard it in Norwegian waters.
  • B. Altmark chosen
    Altmark is a historic region in northern Saxony-Anhalt, Germany, known as one of the original heartlands of the medieval Margraviate of Brandenburg.
  • C. Brackenfell
    Brackenfell is a residential suburb in the northern part of Cape Town, South Africa, known for its family-friendly neighborhoods and proximity to major transport routes and shopping centers.
  • D. Umberleigh
    Umberleigh is a small rural village in North Devon, England, situated on the River Taw and served by a local railway station.
  • E. Mauregard
    Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15661046c819097a53de2a3e0443b completed April 16, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0592b5c8190a4597644864a6bcb completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:52 a.m.