Triple

T8353574
Position Surface form Disambiguated ID Type / Status
Subject Little Poland (Greenpoint) E196620 entity
Predicate alternativeName P39 FINISHED
Object Polish Greenpoint E727548 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: Polish Greenpoint | Statement: [Little Poland (Greenpoint), alternativeName, Polish Greenpoint]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polish Greenpoint
Context triple: [Little Poland (Greenpoint), alternativeName, Polish Greenpoint]
  • A. Little Poland in Greenpoint chosen
    Little Poland in Greenpoint is a Brooklyn neighborhood enclave known for its dense Polish-American community, traditional eateries, and cultural shops.
  • B. Ostrower
    Ostrower is the surname of Fayga Ostrower, a notable Polish-born Brazilian artist and printmaker.
  • C. Nikolaiviertel
    Nikolaiviertel is a historic quarter in central Berlin known for its reconstructed medieval-style streets, traditional German restaurants, and proximity to the Spree River.
  • D. Silesia quarter
    The Silesia quarter is a heraldic section of the Liechtenstein coat of arms that represents the historical ties of the princely family to the Silesian region.
  • E. Mokotów
    Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb804756088190a766e1a486ccfdff completed March 31, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7b2d00c8190b7df13a0853a6374 completed April 2, 2026, 3:51 a.m.
Created at: March 30, 2026, 5:59 p.m.