Triple

T16039018
Position Surface form Disambiguated ID Type / Status
Subject Iller E389043 entity
Predicate locatedIn P40 FINISHED
Object Swabia (Bavaria) E64457 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: Swabia (Bavaria) | Statement: [Iller, locatedIn, Swabia (Bavaria)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swabia (Bavaria)
Context triple: [Iller, locatedIn, Swabia (Bavaria)]
  • A. Swabia (Bavaria) chosen
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • B. Bavaria
    Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
  • C. Baviera
    Baviera is a barangay, or local administrative village, within the city of Sagay in the Philippines.
  • D. Bavaria and Carinthia
    Bavaria and Carinthia are neighboring regions of Germany and Austria, respectively, that meet along a portion of the Germany–Austria border.
  • E. Franconia
    Franconia is a historical region in northern Bavaria, Germany, known for its medieval towns, rich cultural heritage, and distinct Franconian identity within the German-speaking world.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833eb90c8190b10dca3ce0793ddf completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff796fafc8190b6cfb2d8ea502eef completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 4:56 a.m.