Triple

T38094240
Position Surface form Disambiguated ID Type / Status
Subject Duchy of Courland over Tobago E951200 entity
Predicate primarySettlement P13187 FINISHED
Object Fort Casimir
Fort Casimir was the main colonial stronghold and administrative center established by the Duchy of Courland on the Caribbean island of Tobago in the 17th century.
E2256983 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: Fort Casimir | Statement: [Duchy of Courland over Tobago, primarySettlement, Fort Casimir]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Fort Casimir
Triple: [Duchy of Courland over Tobago, primarySettlement, Fort Casimir]
Generated description
Fort Casimir was the main colonial stronghold and administrative center established by the Duchy of Courland on the Caribbean island of Tobago in the 17th century.

Provenance (5 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_69f76f04960c8190a83f14ae4c67f5bc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc458abc7c819099a0d0a3f05c6285 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41680c11748190b11a90beff8017f8 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a416bdd755c8190951cb9fa84a487a0 completed June 28, 2026, 6:45 p.m.
NED2 Entity disambiguation (via description) batch_6a416cd609088190b91e9b633fe67918 completed June 28, 2026, 6:49 p.m.
Created at: May 3, 2026, 4:21 p.m.