Triple

T30204072
Position Surface form Disambiguated ID Type / Status
Subject Chief Justice of Liberia E767861 entity
Predicate officeHoldersInclude P537 FINISHED
Object Sie-A-Nyene G. Yuoh
Sie-A-Nyene G. Yuoh is a Liberian jurist who serves as the Chief Justice of the Supreme Court of Liberia.
 E1904588 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: Sie-A-Nyene G. Yuoh | Statement: [Chief Justice of Liberia, officeHoldersInclude, Sie-A-Nyene G. Yuoh]
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: Sie-A-Nyene G. Yuoh
Triple: [Chief Justice of Liberia, officeHoldersInclude, Sie-A-Nyene G. Yuoh]
Generated description
Sie-A-Nyene G. Yuoh is a Liberian jurist who serves as the Chief Justice of the Supreme Court of Liberia.

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_69f2247eb0848190b4032f302d39c0d9 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67fc7921081909b4c17550cb08845 completed May 2, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2758a2e2e4819099eb528a15d2bfa2 completed June 9, 2026, 12:04 a.m.
NEDg Description generation batch_6a275a7f3e7c8190bd79a2bad2e66ca1 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275e9f9f148190ab1d1fd5ebc2d6bd completed June 9, 2026, 12:30 a.m.
Created at: April 29, 2026, 7:31 p.m.