Triple

T27349377
Position Surface form Disambiguated ID Type / Status
Subject Jeffrey Bell E684313 entity
Predicate workedOn P3 FINISHED
Object The Chronicle
The Chronicle is an American television series, best known as a sci-fi/comedy-drama about reporters at a tabloid newspaper that covers real supernatural events.
 E1766010 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: The Chronicle | Statement: [Jeffrey Bell, workedOn, The Chronicle]
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: The Chronicle
Triple: [Jeffrey Bell, workedOn, The Chronicle]
Generated description
The Chronicle is an American television series, best known as a sci-fi/comedy-drama about reporters at a tabloid newspaper that covers real supernatural events.

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_69ef1480a76481908684256ddd5bfda3 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62ba6aeb08190a6c504a508911d1f completed May 2, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129ccd6fc08190adb59b21555f7029 completed May 24, 2026, 6:38 a.m.
NEDg Description generation batch_6a129da51ce08190b85045a3d378c25f completed May 24, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_6a129e4151208190995590e78cf35502 completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:47 a.m.