Triple

T35344806
Position Surface form Disambiguated ID Type / Status
Subject Minister of National Security of Grenada E1020710 entity
Predicate officeHeldBy P537 FINISHED
Object Tillman Thomas
Tillman Thomas is a Grenadian politician and former Prime Minister who has held several key government positions, including leadership roles in national security.
E2137066 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: Tillman Thomas | Statement: [Minister of National Security of Grenada, officeHeldBy, Tillman Thomas]
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: Tillman Thomas
Triple: [Minister of National Security of Grenada, officeHeldBy, Tillman Thomas]
Generated description
Tillman Thomas is a Grenadian politician and former Prime Minister who has held several key government positions, including leadership roles in national security.

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_69f76decd95c8190ae428f6a19d535de completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7915d005c8190b81056acf734fc67 completed May 3, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3823d02c1c8190b96473ed3600bd93 completed June 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a38245284ec8190bf354cdef8171baf completed June 21, 2026, 5:50 p.m.
NED2 Entity disambiguation (via description) batch_6a3826cdcc308190bffdc6badba70875 completed June 21, 2026, 6 p.m.
Created at: May 3, 2026, 4:03 p.m.