Triple

T9943602
Position Surface form Disambiguated ID Type / Status
Subject Komaba E194143 entity
Predicate hasPark P105 FINISHED
Object Komaba Park E270283 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: Komaba Park | Statement: [Komaba, hasPark, Komaba Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komaba Park
Context triple: [Komaba, hasPark, Komaba Park]
  • A. Komaba Park chosen
    Komaba Park is a public green space in Tokyo’s Meguro ward known for its tranquil gardens, historic residences, and seasonal cherry blossoms.
  • B. Tsurumai Park
    Tsurumai Park is a historic public park in Nagoya, Japan, known for its cherry blossoms, landscaped grounds, and cultural facilities.
  • C. Tsukisamu Park
    Tsukisamu Park is a large public park in Sapporo, Japan, known for its expansive green spaces, sports facilities, and seasonal recreational activities.
  • D. Yamashita Park
    Yamashita Park is a famous seaside public park in Yokohama, Japan, known for its waterfront promenade, harbor views, and historic landmarks.
  • E. Kinshi Park
    Kinshi Park is a popular urban green space in Tokyo’s Kinshichō district, known for its cherry blossoms, sports facilities, and views of Tokyo Skytree.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb613fbb48190b82a06987310cc96 completed April 2, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e531dfa48190b57fcd2444de1ab7 completed April 5, 2026, 10:41 p.m.
Created at: March 30, 2026, 8:45 p.m.