Triple

T1730712
Position Surface form Disambiguated ID Type / Status
Subject Second Liberian Civil War E37802 entity
Predicate location P40 FINISHED
Object Monrovia E37770 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: Monrovia | Statement: [Second Liberian Civil War, location, Monrovia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monrovia
Context triple: [Second Liberian Civil War, location, Monrovia]
  • A. Monrovia chosen
    Monrovia is the largest city and main economic and administrative center of Liberia, located on the Atlantic coast in West Africa.
  • B. Freetown
    Freetown is the capital and largest city of Sierra Leone, known as a historic port and former center for resettled freed slaves in West Africa.
  • C. Freetown
    Freetown is a historic rural town in Bristol County, southeastern Massachusetts, known for its forests, ponds, and the reputedly haunted Freetown-Fall River State Forest.
  • D. Banjul
    Banjul is the capital and principal port city of The Gambia, located on an island at the mouth of the Gambia River in West Africa.
  • E. Roseau
    Roseau is the largest city and main commercial and administrative center of the Caribbean island nation of Dominica.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa637f202c8190b46a31bef51465c8 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada980ec888190b78726012e50c905 completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:30 p.m.