Triple

T25465612
Position Surface form Disambiguated ID Type / Status
Subject President of CNN Productions E638162 entity
Predicate reportsTo P258 FINISHED
Object CNN executive leadership
CNN executive leadership is the senior management team responsible for setting the network’s strategic direction, overseeing its global news operations, and guiding its business and editorial priorities.
 E1680671 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: CNN executive leadership | Statement: [President of CNN Productions, reportsTo, CNN executive leadership]
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: CNN executive leadership
Triple: [President of CNN Productions, reportsTo, CNN executive leadership]
Generated description
CNN executive leadership is the senior management team responsible for setting the network’s strategic direction, overseeing its global news operations, and guiding its business and editorial priorities.

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_69e75db8bab08190baca80b4a8c315fd completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f74c5df88190a683cddba03a7afe completed May 2, 2026, 1:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1089b7171c8190b5e5a044320080f3 completed May 22, 2026, 4:52 p.m.
NEDg Description generation batch_6a108b354e148190abe0738535723e38 completed May 22, 2026, 4:58 p.m.
NED2 Entity disambiguation (via description) batch_6a108bc789948190bca50782a54091f8 completed May 22, 2026, 5 p.m.
Created at: April 21, 2026, 2:14 p.m.