Triple

T8504239
Position Surface form Disambiguated ID Type / Status
Subject Lisa Gardner E201293 entity
Predicate hasWritten P2831 FINISHED
Object Gone
"Gone" is a suspense thriller novel by bestselling American crime writer Lisa Gardner, featuring a high-stakes kidnapping investigation and psychological tension.
 E739279 NE FINISHED

How this triple was built (4 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: Gone | Statement: [Lisa Gardner, hasWritten, Gone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gone
Context triple: [Lisa Gardner, hasWritten, Gone]
  • A. Gone
    "Gone" is a reflective hip-hop track by Kanye West featuring Consequence and Cam'ron, known for its soulful Otis Redding sample and intricate storytelling.
  • B. Gone
    "Gone" is a country music album by American singer-songwriter Dwight Yoakam that blends traditional honky-tonk with more contemporary influences.
  • C. Gone
    "Gone" is a popular R&B-influenced ballad by American boy band *NSYNC, known for its emotional lyrics and Justin Timberlake's prominent lead vocals.
  • D. Gone
    "Gone" is a U2 song from their 1997 album "Pop," known for its introspective lyrics and powerful live performances.
  • E. Gone
    "Gone" is a crime thriller novel in the Michael Bennett series by James Patterson, following the NYPD detective as he confronts a vengeful crime lord he once helped put away.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Gone
Triple: [Lisa Gardner, hasWritten, Gone]
Generated description
"Gone" is a suspense thriller novel by bestselling American crime writer Lisa Gardner, featuring a high-stakes kidnapping investigation and psychological tension.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gone
Target entity description: "Gone" is a suspense thriller novel by bestselling American crime writer Lisa Gardner, featuring a high-stakes kidnapping investigation and psychological tension.
  • A. Gone
    "Gone" is a reflective hip-hop track by Kanye West featuring Consequence and Cam'ron, known for its soulful Otis Redding sample and intricate storytelling.
  • B. Gone
    "Gone" is a country music album by American singer-songwriter Dwight Yoakam that blends traditional honky-tonk with more contemporary influences.
  • C. Gone
    "Gone" is a popular R&B-influenced ballad by American boy band *NSYNC, known for its emotional lyrics and Justin Timberlake's prominent lead vocals.
  • D. Gone
    "Gone" is a U2 song from their 1997 album "Pop," known for its introspective lyrics and powerful live performances.
  • E. Gone
    "Gone" is a crime thriller novel in the Michael Bennett series by James Patterson, following the NYPD detective as he confronts a vengeful crime lord he once helped put away.
  • F. None of above. chosen

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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe59d67d081908155a43b9b463fe3 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e26a3108190a48b00c2927be971 completed April 2, 2026, 11:08 a.m.
NEDg Description generation batch_69ce4ff88ff48190a5641635187a9e4f completed April 2, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69ce50fd3150819097562093bee78a6d completed April 2, 2026, 11:20 a.m.
Created at: March 30, 2026, 6:14 p.m.