Triple

T18246629
Position Surface form Disambiguated ID Type / Status
Subject Old Riga E436967 entity
Predicate hasPart P35 FINISHED
Object Swedish Gate NE NERFINISHED

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: Swedish Gate | Statement: [Old Riga, hasPart, Swedish Gate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swedish Gate
Context triple: [Old Riga, hasPart, Swedish Gate]
  • A. Swedish Gate chosen
    Swedish Gate is a historic city gate in Riga’s Old Town, notable as one of the few remaining medieval entrances to the former fortified city.
  • B. Norway Gate
    Norway Gate is a historic entrance structure associated with the Kastellet fortress complex.
  • C. Musegg Gate
    Musegg Gate is one of the historic towers and entrances incorporated into Lucerne’s medieval Musegg Wall fortifications in Switzerland.
  • D. Narva Gate
    Narva Gate is a historic triumphal arch in Saint Petersburg, Russia, commemorating Russian military victories and serving as a notable architectural landmark.
  • E. Londorossi Gate
    Londorossi Gate is a primary western entrance and registration point to Mount Kilimanjaro National Park, commonly used by climbers beginning the Lemosho Route.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e7d49c8190b227a13b63615754 completed April 19, 2026, 3:42 p.m.
Created at: April 10, 2026, 10:33 a.m.