Triple

T13018976
Position Surface form Disambiguated ID Type / Status
Subject Kota Pahlawan E322625 entity
Predicate linkedToHistoricalFigure P26467 FINISHED
Object Bung Tomo E605429 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: Bung Tomo | Statement: [Kota Pahlawan, linkedToHistoricalFigure, Bung Tomo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bung Tomo
Context triple: [Kota Pahlawan, linkedToHistoricalFigure, Bung Tomo]
  • A. Bung Tomo chosen
    Bung Tomo was an Indonesian nationalist leader and orator renowned for rallying resistance against British and Dutch forces during the 1945 Battle of Surabaya.
  • B. Tajōmaru
    Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
  • C. Toma-no-mimi
    Toma-no-mimi is one of the twin main peaks forming the summit area of Mount Tanigawa in Japan’s Tanigawa mountain range.
  • D. Tebunginako
    Tebunginako is a village settlement on the atoll of Abaiang in the island nation of Kiribati, known for being severely affected by coastal erosion and sea-level rise.
  • E. Bungotakada
    Bungotakada is a small coastal city in northeastern Kyushu, Japan, known for its preserved Showa-era townscape and scenic rural landscapes.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ece22908190a0941e23df7c774d completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c116423881908d0de1e04904fbc3 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:51 p.m.