Triple

T10366536
Position Surface form Disambiguated ID Type / Status
Subject Everest (2015 film) E244263 entity
Predicate basedOn P98 FINISHED
Object Climbing High
Climbing High is a non-fiction book by British mountaineer and writer Lene Gammelgaard that recounts her experiences on the 1996 Mount Everest disaster expedition.
 E859374 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: Climbing High | Statement: [Everest (2015 film), basedOn, Climbing High]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Climbing High
Context triple: [Everest (2015 film), basedOn, Climbing High]
  • A. The Climb
    "The Climb" is a pop ballad by Miley Cyrus that became widely known as an inspirational anthem about perseverance and self-discovery.
  • B. Climb
    "Climb" is a track by Mos Def from his acclaimed hip-hop album *Black on Both Sides*.
  • C. So High
    "So High" is an R&B/soul song by John Legend from his debut album "Get Lifted."
  • D. So High
    "So High" is a creative work associated with DeVon Harris, likely recognized as one of his most prominent or influential projects.
  • E. I'd Climb the Highest Mountain
    "I'd Climb the Highest Mountain" is a 1951 American drama film set in rural Georgia, following a newly arrived minister and his wife as they adjust to and inspire their small mountain community.
  • 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: Climbing High
Triple: [Everest (2015 film), basedOn, Climbing High]
Generated description
Climbing High is a non-fiction book by British mountaineer and writer Lene Gammelgaard that recounts her experiences on the 1996 Mount Everest disaster expedition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Climbing High
Target entity description: Climbing High is a non-fiction book by British mountaineer and writer Lene Gammelgaard that recounts her experiences on the 1996 Mount Everest disaster expedition.
  • A. The Climb
    "The Climb" is a pop ballad by Miley Cyrus that became widely known as an inspirational anthem about perseverance and self-discovery.
  • B. Climb
    "Climb" is a track by Mos Def from his acclaimed hip-hop album *Black on Both Sides*.
  • C. So High
    "So High" is an R&B/soul song by John Legend from his debut album "Get Lifted."
  • D. So High
    "So High" is a creative work associated with DeVon Harris, likely recognized as one of his most prominent or influential projects.
  • E. I'd Climb the Highest Mountain
    "I'd Climb the Highest Mountain" is a 1951 American drama film set in rural Georgia, following a newly arrived minister and his wife as they adjust to and inspire their small mountain community.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e96fd6f081908f630a16106996d9 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7953ba52881908d6d7e5b099c12d2 completed April 9, 2026, 12:02 p.m.
NEDg Description generation batch_69d79784baa481909e57adda27578cc2 completed April 9, 2026, 12:11 p.m.
NED2 Entity disambiguation (via description) batch_69d7989f8dfc8190b1fe4429f7bb0283 completed April 9, 2026, 12:16 p.m.
Created at: April 6, 2026, noon