Triple

T15184753
Position Surface form Disambiguated ID Type / Status
Subject The Public Enemy E362838 entity
Predicate basedOn P98 FINISHED
Object Beer and Blood
Beer and Blood is a crime novel that served as the literary basis for the classic gangster film "The Public Enemy."
 E1141272 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: Beer and Blood | Statement: [The Public Enemy, basedOn, Beer and Blood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beer and Blood
Context triple: [The Public Enemy, basedOn, Beer and Blood]
  • A. The Man Who Loved Beer
    "The Man Who Loved Beer" is a song by British singer-songwriter David Byrne, featured on his 2004 album *Grown Backwards*.
  • B. Drink a Beer
    "Drink a Beer" is a reflective country ballad by Luke Bryan that poignantly addresses loss and remembrance.
  • C. Beer for My Horses
    "Beer for My Horses" is a popular country song by Toby Keith featuring Willie Nelson, known for its outlaw justice theme and later adapted into a comedy film of the same name.
  • D. Un bon bock
    Un bon bock is an early French animated film created by pioneer Émile Reynaud, known for its hand-drawn images projected using his Théâtre Optique system.
  • E. 2 Cups of Blood
    2 Cups of Blood is a horrorcore rap track by the group Gravediggaz from their debut album "Niggamortis" (also known as "6 Feet Deep").
  • 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: Beer and Blood
Triple: [The Public Enemy, basedOn, Beer and Blood]
Generated description
Beer and Blood is a crime novel that served as the literary basis for the classic gangster film "The Public Enemy."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Beer and Blood
Target entity description: Beer and Blood is a crime novel that served as the literary basis for the classic gangster film "The Public Enemy."
  • A. The Man Who Loved Beer
    "The Man Who Loved Beer" is a song by British singer-songwriter David Byrne, featured on his 2004 album *Grown Backwards*.
  • B. Drink a Beer
    "Drink a Beer" is a reflective country ballad by Luke Bryan that poignantly addresses loss and remembrance.
  • C. Beer for My Horses
    "Beer for My Horses" is a popular country song by Toby Keith featuring Willie Nelson, known for its outlaw justice theme and later adapted into a comedy film of the same name.
  • D. Un bon bock
    Un bon bock is an early French animated film created by pioneer Émile Reynaud, known for its hand-drawn images projected using his Théâtre Optique system.
  • E. 2 Cups of Blood
    2 Cups of Blood is a horrorcore rap track by the group Gravediggaz from their debut album "Niggamortis" (also known as "6 Feet Deep").
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006674c088190ba635a78c30f5637 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec893f1e08190a192b7b9b80484e8 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec91a2d708190bcc67793c46b2a61 completed May 9, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_69feca0d38088190910dbf4f2538a9d4 completed May 9, 2026, 5:45 a.m.
Created at: April 10, 2026, 3:09 a.m.