Triple

T11263585
Position Surface form Disambiguated ID Type / Status
Subject Lichtenburg E266624 entity
Predicate hasVariantSpelling P457 FINISHED
Object Lichtenberg E786931 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: Lichtenberg | Statement: [Lichtenburg, hasVariantSpelling, Lichtenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichtenberg
Context triple: [Lichtenburg, hasVariantSpelling, Lichtenberg]
  • A. Lichtenberg
    Lichtenberg is a borough in eastern Berlin, Germany, known for its mix of residential areas, historical sites, and former Soviet administrative and military facilities.
  • B. Lichtenburg chosen
    Lichtenburg is a town in South Africa’s North West Province, historically significant in the Second Anglo-Boer War and later known for its diamond discoveries and agricultural activity.
  • C. Willenberg
    Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
  • D. Reichenbach
    Reichenbach is a German surname most notably associated with Hans Reichenbach, a prominent 20th-century philosopher of science and logical empiricist.
  • E. Witellikon
    Witellikon is a small settlement within the municipality of Küsnacht in the canton of Zürich, Switzerland, situated along the shores of Lake Zurich.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e94d56048190bf808e1bc2188714 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ccba233481909f00ebe2237c4f0c completed April 19, 2026, 12:38 p.m.
Created at: April 8, 2026, 9:31 p.m.