Triple

T16201600
Position Surface form Disambiguated ID Type / Status
Subject Papingo E393213 entity
Predicate near P350 FINISHED
Object Astraka Towers E1199612 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: Astraka Towers | Statement: [Papingo, near, Astraka Towers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Astraka Towers
Context triple: [Papingo, near, Astraka Towers]
  • A. Astraka Towers chosen
    Astraka Towers is a striking series of steep limestone peaks in the Pindus Mountains of northwestern Greece, popular with hikers and climbers for its dramatic cliffs and alpine scenery.
  • B. Broel Towers
    Broel Towers are a pair of medieval defensive towers and an iconic historical symbol of the Belgian city of Kortrijk (Courtrai).
  • C. Octan Tower
    Octan Tower is the central skyscraper base of operations for the fictional fuel and energy conglomerate Octan in The LEGO Movie universe.
  • D. Granovitaya Tower
    Granovitaya Tower is a historic defensive tower that forms part of the medieval Kolomna Kremlin fortress in Russia.
  • E. Nina Tower
    Nina Tower is a prominent skyscraper complex in Tsuen Wan, Hong Kong, known for its distinctive twin-tower design and mixed-use commercial and hotel facilities.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2270aa7f08190ab37aa9ff46816fc completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00078db04081909f7e14b09687ba67 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.