Triple

T7165565
Position Surface form Disambiguated ID Type / Status
Subject Fort Dansborg E167059 entity
Predicate location P40 FINISHED
Object Tranquebar E123168 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: Tranquebar | Statement: [Fort Dansborg, location, Tranquebar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tranquebar
Context triple: [Fort Dansborg, location, Tranquebar]
  • A. Tranquebar chosen
    Tranquebar is a historic coastal town in Tamil Nadu, India, known for its former Danish colonial settlement and distinctive Indo-European architecture.
  • B. Madras Port
    Madras Port, now known as Chennai Port, is one of India’s oldest and busiest seaports, serving as a key maritime gateway on the southeastern coast of the country.
  • C. Laboe
    Laboe is a seaside town in northern Germany known for its Baltic Sea beaches and the Laboe Naval Memorial overlooking Kiel Bay.
  • D. Ostend
    Ostend is a Belgian coastal city on the North Sea known for its beaches, port, and seaside tourism.
  • E. Ostend
    Ostend is a small residential and commercial settlement on Waiheke Island in New Zealand’s Hauraki Gulf.
  • 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_69c68888c10c819095e0383020225758 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e832d2548190aacff0de80dbc268 completed March 27, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7adcc145c8190ba65831ed891a225 completed March 28, 2026, 10:30 a.m.
Created at: March 27, 2026, 2:47 p.m.