Triple

T16439498
Position Surface form Disambiguated ID Type / Status
Subject Songs for Polarbears E399260 entity
Predicate hasPart P35 FINISHED
Object Make Up
"Make Up" is a song by the Scottish rock band Snow Patrol, featured on their debut studio album "Songs for Polarbears."
E1213687 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: Make Up | Statement: [Songs for Polarbears, hasPart, Make Up]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Make Up
Context triple: [Songs for Polarbears, hasPart, Make Up]
  • A. Make Up For Ever
    Make Up For Ever is a professional cosmetics brand known for its high-performance makeup products widely used by makeup artists and beauty enthusiasts.
  • B. Lipstick
    Lipstick is a 1976 American thriller film known for its controversial depiction of sexual assault and revenge, starring Margaux Hemingway in her film debut.
  • C. Lipstick
    "Lipstick" is a pop-R&B song by British singer and television personality Alesha Dixon, released during her early solo career after Mis-Teeq.
  • D. War Paint
    War Paint is a Broadway musical that dramatizes the rivalry between cosmetics titans Helena Rubinstein and Elizabeth Arden in mid-20th-century America.
  • E. The Basis of Make-Up
    The Basis of Make-Up is an experimental film project by Heinz Emigholz that meticulously documents and visually interprets his sketchbooks, blending drawing, text, and cinematic form.
  • 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: Make Up
Triple: [Songs for Polarbears, hasPart, Make Up]
Generated description
"Make Up" is a song by the Scottish rock band Snow Patrol, featured on their debut studio album "Songs for Polarbears."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Make Up
Target entity description: "Make Up" is a song by the Scottish rock band Snow Patrol, featured on their debut studio album "Songs for Polarbears."
  • A. Make Up For Ever
    Make Up For Ever is a professional cosmetics brand known for its high-performance makeup products widely used by makeup artists and beauty enthusiasts.
  • B. Lipstick
    Lipstick is a 1976 American thriller film known for its controversial depiction of sexual assault and revenge, starring Margaux Hemingway in her film debut.
  • C. Lipstick
    "Lipstick" is a pop-R&B song by British singer and television personality Alesha Dixon, released during her early solo career after Mis-Teeq.
  • D. War Paint
    War Paint is a Broadway musical that dramatizes the rivalry between cosmetics titans Helena Rubinstein and Elizabeth Arden in mid-20th-century America.
  • E. The Basis of Make-Up
    The Basis of Make-Up is an experimental film project by Heinz Emigholz that meticulously documents and visually interprets his sketchbooks, blending drawing, text, and cinematic form.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba720a48190b0b412225e993e52 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458dde8881909778c9964ddc8efa completed May 10, 2026, 8:45 a.m.
NEDg Description generation batch_6a00472cdc2881908211045515cd21ee completed May 10, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_6a0047b4b6688190afef52b39788ceae completed May 10, 2026, 8:54 a.m.
Created at: April 10, 2026, 5:10 a.m.