Triple

T1663840
Position Surface form Disambiguated ID Type / Status
Subject Málaga E35967 entity
Predicate historicalName P65 FINISHED
Object Malaca E187460 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: Malaca | Statement: [Málaga, historicalName, Malaca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malaca
Context triple: [Málaga, historicalName, Malaca]
  • A. Malaka chosen
    Malaka is the ancient Phoenician and later Roman name for the city now known as Málaga in southern Spain.
  • B. Malacca
    Malacca is a historic Malaysian state on the southwest coast of the Malay Peninsula, renowned for its rich multicultural heritage and its former role as a major trading port.
  • C. Macassar
    Macassar is the former name of Makassar, a major port city on the island of Sulawesi in Indonesia known historically as an important center of trade and maritime power.
  • D. Labuan
    Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
  • E. Labuan
    Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
  • 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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90ad958f48190a6344e1be78b574d completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71adb0388190b358e83fa8dfaef5 completed March 8, 2026, 12:55 p.m.
Created at: March 4, 2026, 7:29 p.m.