Triple

T6869117
Position Surface form Disambiguated ID Type / Status
Subject Flachgau E158492 entity
Predicate contains P35 FINISHED
Object Mattsee E502059 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: Mattsee | Statement: [Flachgau, contains, Mattsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mattsee
Context triple: [Flachgau, contains, Mattsee]
  • A. Mattsee chosen
    Mattsee is a picturesque market town in the Austrian state of Salzburg, known for its lakeside setting, historic abbey, and well-preserved medieval center.
  • B. Mustvee
    Mustvee is a small Estonian town on the northern shore of Lake Peipus, known historically as a fishing and trading settlement with a mixed Estonian and Russian Old Believer community.
  • C. Matemale
    Matemale is a small commune in the Pyrénées-Orientales department of southern France, known for its high-altitude lake and mountain setting in the Capcir plateau.
  • D. Megeb
    Megeb is a dialect of the Dargin language spoken by the Dargin people of the North Caucasus region in Dagestan, Russia.
  • E. Teisen
    Teisen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green spaces, and convenient access to public transportation.
  • 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_69c68831e3648190a643c328122e4d43 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8a916a88190b81551731dff2898 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74299ae148190a56c7b1ee8829f40 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.