Triple

T2916971
Position Surface form Disambiguated ID Type / Status
Subject Orłowo E78629 entity
Predicate hasLandmark P105 FINISHED
Object Orłowo Pier E78629 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: Orłowo Pier | Statement: [Orłowo, hasLandmark, Orłowo Pier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orłowo Pier
Context triple: [Orłowo, hasLandmark, Orłowo Pier]
  • A. Orłowo chosen
    Orłowo is a coastal district of Gdynia in northern Poland, known for its scenic cliffs, pier, and Baltic Sea beaches.
  • B. Orzysz
    Orzysz is a small town in northeastern Poland known for its lakeside setting and proximity to extensive forests and military training grounds.
  • C. Wejherowo
    Wejherowo is a historic town in northern Poland known for its baroque Calvary complex and role as a local cultural and administrative center.
  • D. Oleśnica
    Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
  • E. Mierzanowo
    Mierzanowo is a village in Poland notable as the birthplace of Ignacy Mościcki, the country's pre-World War II president and chemist.
  • 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a2bdd88190aa01c26a27f9afbd completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0562847488190a0d6b7de99796cd9 completed March 10, 2026, 5:34 p.m.
Created at: March 8, 2026, 2:53 p.m.