Triple

T9209111
Position Surface form Disambiguated ID Type / Status
Subject Marienfelde E221065 entity
Predicate borderedBy P224 FINISHED
Object Lichtenrade E213050 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: Lichtenrade | Statement: [Marienfelde, borderedBy, Lichtenrade]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichtenrade
Context triple: [Marienfelde, borderedBy, Lichtenrade]
  • A. Lichtenrade chosen
    Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
  • B. Kozelsk
    Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
  • C. Zvenigorod
    Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
  • D. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • E. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • 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_69ca83e9d0e081908bdb71097201a06c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd9b3c8c081909a688ce699928fc0 completed April 1, 2026, 8:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065e967508190acb962d37c390d68 completed April 4, 2026, 1:14 a.m.
Created at: March 30, 2026, 7:26 p.m.