Triple

T2009887
Position Surface form Disambiguated ID Type / Status
Subject Tug of War E43665 entity
Predicate recordedInCity P8088 FINISHED
Object Montserrat E17737 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: Montserrat | Statement: [Tug of War, recordedInCity, Montserrat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montserrat
Context triple: [Tug of War, recordedInCity, Montserrat]
  • A. Montserrat chosen
    Montserrat is a small Caribbean island and British Overseas Territory known for its volcanic activity and lush, mountainous landscape.
  • B. Serra
    Serra is a Spanish surname most famously associated with Junípero Serra, the 18th-century Franciscan friar who founded several missions in what is now California.
  • C. Morne la Selle
    Morne la Selle is the highest mountain in Haiti, located in the southern part of the country.
  • D. Mount Aigaleo
    Mount Aigaleo is a low mountain range in the Attica region of Greece, west of Athens, known for its historical and strategic significance overlooking the ancient battlefield of Salamis.
  • E. Mount Pico
    Mount Pico is a prominent stratovolcano on Pico Island in the Azores and the highest peak in Portugal.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8afe6f8819092679c86d1f2d041 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ae5f0748190aecee47884c61ecc completed March 8, 2026, 11:48 p.m.
Created at: March 4, 2026, 7:37 p.m.