Triple

T37806490
Position Surface form Disambiguated ID Type / Status
Subject Jeffery Deaver E942515 entity
Predicate notableWork P4 FINISHED
Object The Empty Chair
The Empty Chair is a crime thriller novel by Jeffery Deaver featuring forensic detective Lincoln Rhyme as he investigates a series of abductions in rural North Carolina.
 E2244319 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 Empty Chair | Statement: [Jeffery Deaver, notableWork, The Empty Chair]
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 Empty Chair
Triple: [Jeffery Deaver, notableWork, The Empty Chair]
Generated description
The Empty Chair is a crime thriller novel by Jeffery Deaver featuring forensic detective Lincoln Rhyme as he investigates a series of abductions in rural North Carolina.

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_69f76ee8104c8190ab17133ccd8f86e6 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb198a09c8190a0154f9ead42d7da completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40f18ffb088190ad4e659181180671 completed June 28, 2026, 10:04 a.m.
NEDg Description generation batch_6a40f580ca8c81908065aebedf0280f8 completed June 28, 2026, 10:20 a.m.
NED2 Entity disambiguation (via description) batch_6a40f5ff32d88190b0595dc6f2ada218 completed June 28, 2026, 10:22 a.m.
Created at: May 3, 2026, 4:19 p.m.