Triple

T27074266
Position Surface form Disambiguated ID Type / Status
Subject Counter Terrorism Service (Iraq) E685413 entity
Predicate trainingSupportFrom P3665 FINISHED
Object Jordan
Jordan is a Middle Eastern country known for its strategic geopolitical role, security cooperation with Western and regional partners, and relatively stable governance in a turbulent region.
E11658 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: Jordan | Statement: [Counter Terrorism Service (Iraq), trainingSupportFrom, Jordan]
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: Jordan
Triple: [Counter Terrorism Service (Iraq), trainingSupportFrom, Jordan]
Generated description
Jordan is a Middle Eastern country known for its strategic geopolitical role, security cooperation with Western and regional partners, and relatively stable governance in a turbulent region.

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_69ef14843b1481909d828b3d5a44550a completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62314899c8190a8d6c7175efc2dec completed May 2, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ada0dc48190a8f0b839c1860c01 completed May 23, 2026, 11:40 p.m.
NEDg Description generation batch_6a123baa5c608190908cb92bee2e9cb2 completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c6a4e4481908d79c547106ba5f0 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 8:30 a.m.