Triple

T14213874
Position Surface form Disambiguated ID Type / Status
Subject Nicola Shindler E352297 entity
Predicate notableWork P4 FINISHED
Object Stay Close
Stay Close is a British crime drama television series based on Harlan Coben’s novel of the same name, following the intertwined lives of four people whose dark secrets resurface.
 E1086067 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: Stay Close | Statement: [Nicola Shindler, notableWork, Stay Close]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stay Close
Context triple: [Nicola Shindler, notableWork, Stay Close]
  • A. Come Close
    "Come Close" is a soulful hip-hop single by Common, produced by The Neptunes and known for its intimate, romantic lyrics.
  • B. Too Close
    "Too Close" is a 1998 R&B hit single by American group Next, best known for its sensual lyrics and chart-topping success.
  • C. Too Close
    "Too Close" is a 2011 electro-soul song by British singer Alex Clare that gained widespread popularity after being featured in a major Internet Explorer commercial.
  • D. So Close
    So Close is a popular song by South Korean singer JR, recognized as one of his standout solo releases.
  • E. So Close
    "So Close" is a popular electronic dance track by German DJ and producer Felix Jaehn, known for its catchy melody and radio-friendly sound.
  • 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: Stay Close
Triple: [Nicola Shindler, notableWork, Stay Close]
Generated description
Stay Close is a British crime drama television series based on Harlan Coben’s novel of the same name, following the intertwined lives of four people whose dark secrets resurface.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stay Close
Target entity description: Stay Close is a British crime drama television series based on Harlan Coben’s novel of the same name, following the intertwined lives of four people whose dark secrets resurface.
  • A. Come Close
    "Come Close" is a soulful hip-hop single by Common, produced by The Neptunes and known for its intimate, romantic lyrics.
  • B. Too Close
    "Too Close" is a 1998 R&B hit single by American group Next, best known for its sensual lyrics and chart-topping success.
  • C. Too Close
    "Too Close" is a 2011 electro-soul song by British singer Alex Clare that gained widespread popularity after being featured in a major Internet Explorer commercial.
  • D. So Close
    So Close is a popular song by South Korean singer JR, recognized as one of his standout solo releases.
  • E. So Close
    "So Close" is a popular electronic dance track by German DJ and producer Felix Jaehn, known for its catchy melody and radio-friendly sound.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de620f07bc81909212dcd1c91b5f95 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1959f3d481909c15730bbd6f4748 completed May 7, 2026, 10:59 p.m.
NEDg Description generation batch_69fd1a88fd948190b5d78a4ca4acdb94 completed May 7, 2026, 11:04 p.m.
NED2 Entity disambiguation (via description) batch_69fd1b2ed7748190b3f787f1b64c8831 completed May 7, 2026, 11:07 p.m.
Created at: April 10, 2026, 1:06 a.m.