Triple

T10310545
Position Surface form Disambiguated ID Type / Status
Subject Gregory Moffett E241875 entity
Predicate notableWork P4 FINISHED
Object Dear Brat
Dear Brat is a 1951 American comedy film and sequel to Dear Ruth, featuring Gregory Moffett in a notable role.
E855659 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: Dear Brat | Statement: [Gregory Moffett, notableWork, Dear Brat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dear Brat
Context triple: [Gregory Moffett, notableWork, Dear Brat]
  • A. The Brat
    The Brat is a 1931 American pre-Code comedy film directed by John Ford, based on a stage play about a spirited young woman who disrupts the lives of an upper-class family.
  • B. Beat on the Brat
    "Beat on the Brat" is a classic punk rock song by the Ramones, known for its catchy simplicity, darkly humorous lyrics, and embodiment of the band's raw early sound.
  • C. Brat
    "Brat" is a track by the British electronic music producer and DJ Insomniac.
  • D. Dear My Friends
    Dear My Friends is a South Korean television drama series that poignantly portrays the lives, friendships, and struggles of a group of elderly friends.
  • E. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • 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: Dear Brat
Triple: [Gregory Moffett, notableWork, Dear Brat]
Generated description
Dear Brat is a 1951 American comedy film and sequel to Dear Ruth, featuring Gregory Moffett in a notable role.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dear Brat
Target entity description: Dear Brat is a 1951 American comedy film and sequel to Dear Ruth, featuring Gregory Moffett in a notable role.
  • A. The Brat
    The Brat is a 1931 American pre-Code comedy film directed by John Ford, based on a stage play about a spirited young woman who disrupts the lives of an upper-class family.
  • B. Beat on the Brat
    "Beat on the Brat" is a classic punk rock song by the Ramones, known for its catchy simplicity, darkly humorous lyrics, and embodiment of the band's raw early sound.
  • C. Brat
    "Brat" is a track by the British electronic music producer and DJ Insomniac.
  • D. Dear My Friends
    Dear My Friends is a South Korean television drama series that poignantly portrays the lives, friendships, and struggles of a group of elderly friends.
  • E. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32ac6c08190b23eb042b3ec284a completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d78ece88190885768c979b038df completed April 9, 2026, 3:31 a.m.
NEDg Description generation batch_69d73186831481909555e2205d8783a7 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d732bfc76c819089287477b54a7b77 completed April 9, 2026, 5:01 a.m.
Created at: April 6, 2026, 11:47 a.m.