Triple

T12990893
Position Surface form Disambiguated ID Type / Status
Subject King of Queens E321902 entity
Predicate hasPart P35 FINISHED
Object Tangerine
"Tangerine" is an episode of the American sitcom "The King of Queens," known for its comedic take on everyday married life in Queens, New York.
E1015797 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: Tangerine | Statement: [King of Queens, hasPart, Tangerine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tangerine
Context triple: [King of Queens, hasPart, Tangerine]
  • A. Tangerine
    Tangerine is a popular Afro-pop song by Nigerian singer Yemi Alade, known for its upbeat rhythm and vibrant, danceable style.
  • B. Tangerine
    "Tangerine" is a funk-infused hip hop track by Big Boi featuring T.I., known for its playful, club-ready sound and appearance on Big Boi’s debut solo album.
  • C. Tangerine
    "Tangerine" is a song by the English indie rock band Glass Animals, known for its dreamy production and introspective lyrics.
  • D. Paradise Road
    Paradise Road is a 1997 war drama film about women prisoners of war in World War II, known for its ensemble cast and portrayal of resilience under Japanese captivity.
  • E. Blow
    Blow is a track by the American heavy metal band Bastard, known for its aggressive sound and raw energy.
  • 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: Tangerine
Triple: [King of Queens, hasPart, Tangerine]
Generated description
"Tangerine" is an episode of the American sitcom "The King of Queens," known for its comedic take on everyday married life in Queens, New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tangerine
Target entity description: "Tangerine" is an episode of the American sitcom "The King of Queens," known for its comedic take on everyday married life in Queens, New York.
  • A. Tangerine
    Tangerine is a popular Afro-pop song by Nigerian singer Yemi Alade, known for its upbeat rhythm and vibrant, danceable style.
  • B. Tangerine
    "Tangerine" is a song by the English indie rock band Glass Animals, known for its dreamy production and introspective lyrics.
  • C. Tangerine
    "Tangerine" is a funk-infused hip hop track by Big Boi featuring T.I., known for its playful, club-ready sound and appearance on Big Boi’s debut solo album.
  • D. Paradise Road
    Paradise Road is a 1997 war drama film about women prisoners of war in World War II, known for its ensemble cast and portrayal of resilience under Japanese captivity.
  • E. Blow
    Blow is a track by the American heavy metal band Bastard, known for its aggressive sound and raw energy.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e7765788190a9503ef055bc30ca completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0fca5e4819086b010fdd1813419 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c20a1eb881908a28dc884c2005ef completed May 3, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f6c34b9ec08190bb29458b6f43c388 completed May 3, 2026, 3:38 a.m.
Created at: April 9, 2026, 8:43 p.m.