Triple

T24459084
Position Surface form Disambiguated ID Type / Status
Subject Ghostwritten E616767 entity
Predicate hasCharacter P2308 FINISHED
Object The Radio DJ
The Radio DJ is a character in the novel "Ghostwritten," serving as a late-night radio host whose show becomes a narrative thread connecting disparate stories and characters.
 E1635014 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 Radio DJ | Statement: [Ghostwritten, hasCharacter, The Radio DJ]
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 Radio DJ
Triple: [Ghostwritten, hasCharacter, The Radio DJ]
Generated description
The Radio DJ is a character in the novel "Ghostwritten," serving as a late-night radio host whose show becomes a narrative thread connecting disparate stories and characters.

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_69e2d7ef9fe08190a0613908758b4e86 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f298c8d854819091f1d92eef02b1b1 completed April 29, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe38aa3a88190aaffda5dcb8d699c completed May 22, 2026, 5:03 a.m.
NEDg Description generation batch_6a0fe4bfcea881909cf308d946a88c4c completed May 22, 2026, 5:08 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe54cbdac8190b45d5570023762c4 completed May 22, 2026, 5:10 a.m.
Created at: April 18, 2026, 2:19 a.m.