Triple

T20410048
Position Surface form Disambiguated ID Type / Status
Subject A-ha E500564 entity
Predicate album P1995 FINISHED
Object Cast in Steel
Cast in Steel is a 2015 studio album by Norwegian synth-pop band A-ha that marked their return after a brief split, blending nostalgic sounds with contemporary production.
 E1429565 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: Cast in Steel | Statement: [A-ha, album, Cast in Steel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cast in Steel
Context triple: [A-ha, album, Cast in Steel]
  • A. Made of Steel
    Made of Steel is a Doctor Who tie-in novel featuring the Tenth Doctor, written for younger readers as part of the Quick Reads initiative.
  • B. Street of Steel
    Street of Steel is a prominent thoroughfare in King’s Landing in the world of *A Song of Ice and Fire*, known for its many smithies and metalworkers.
  • C. Tons of Steel
    Tons of Steel is a song featured on the Grateful Dead’s album "In the Dark."
  • D. Bleeding Steel
    Bleeding Steel is a 2017 Chinese science fiction action film starring Jackie Chan that blends futuristic technology, crime, and high-octane stunts.
  • E. The Steel Remains
    The Steel Remains is a dark, gritty epic fantasy novel by Richard Morgan that blends sword-and-sorcery action with mature themes and subversive takes on genre conventions.
  • 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: Cast in Steel
Triple: [A-ha, album, Cast in Steel]
Generated description
Cast in Steel is a 2015 studio album by Norwegian synth-pop band A-ha that marked their return after a brief split, blending nostalgic sounds with contemporary production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cast in Steel
Target entity description: Cast in Steel is a 2015 studio album by Norwegian synth-pop band A-ha that marked their return after a brief split, blending nostalgic sounds with contemporary production.
  • A. Made of Steel
    Made of Steel is a Doctor Who tie-in novel featuring the Tenth Doctor, written for younger readers as part of the Quick Reads initiative.
  • B. Street of Steel
    Street of Steel is a prominent thoroughfare in King’s Landing in the world of *A Song of Ice and Fire*, known for its many smithies and metalworkers.
  • C. Tons of Steel
    Tons of Steel is a song featured on the Grateful Dead’s album "In the Dark."
  • D. Bleeding Steel
    Bleeding Steel is a 2017 Chinese science fiction action film starring Jackie Chan that blends futuristic technology, crime, and high-octane stunts.
  • E. The Steel Remains
    The Steel Remains is a dark, gritty epic fantasy novel by Richard Morgan that blends sword-and-sorcery action with mature themes and subversive takes on genre conventions.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a3e0c1c8190be39d7f09c839dfa completed April 20, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a087b21cb308190a9313a24a902b44d completed May 16, 2026, 2:11 p.m.
NEDg Description generation batch_6a088015c514819087967845614dd25d completed May 16, 2026, 2:32 p.m.
NED2 Entity disambiguation (via description) batch_6a0880b79edc81908b180db5338f57db completed May 16, 2026, 2:35 p.m.
Created at: April 16, 2026, 11:29 a.m.