Triple

T10293230
Position Surface form Disambiguated ID Type / Status
Subject Memphis Raines E241414 entity
Predicate hasFriend P8712 FINISHED
Object Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
 E855856 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: Tumbler | Statement: [Memphis Raines, hasFriend, Tumbler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tumbler
Context triple: [Memphis Raines, hasFriend, Tumbler]
  • A. Jug
    "Jug" is the widely used nickname for the Republic P-47 Thunderbolt, a rugged and heavily armed American World War II fighter-bomber aircraft.
  • B. the Teapot
    The Teapot is a prominent asterism in the constellation Sagittarius whose stars outline the shape of a traditional teapot in the night sky.
  • C. Bottle
    Bottle is a lightweight Python web framework used for building simple web applications and APIs in a single file.
  • D. Teakettle
    Teakettle is a small village in the Cayo District of central Belize, known as a rural community along the George Price Highway near the Belize River.
  • E. Beaker
    Beaker is a high-strung, squeaky-voiced lab assistant from The Muppets, known for his nervous demeanor and frequent mishaps in scientific experiments.
  • 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: Tumbler
Triple: [Memphis Raines, hasFriend, Tumbler]
Generated description
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tumbler
Target entity description: Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
  • A. Jug
    "Jug" is the widely used nickname for the Republic P-47 Thunderbolt, a rugged and heavily armed American World War II fighter-bomber aircraft.
  • B. the Teapot
    The Teapot is a prominent asterism in the constellation Sagittarius whose stars outline the shape of a traditional teapot in the night sky.
  • C. Bottle
    Bottle is a lightweight Python web framework used for building simple web applications and APIs in a single file.
  • D. Teakettle
    Teakettle is a small village in the Cayo District of central Belize, known as a rural community along the George Price Highway near the Belize River.
  • E. Beaker
    Beaker is a high-strung, squeaky-voiced lab assistant from The Muppets, known for his nervous demeanor and frequent mishaps in scientific experiments.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d46fb08190b7694290692e47dc completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d1c180481909ca9983e14cbb931 completed April 9, 2026, 3:29 a.m.
NEDg Description generation batch_69d73182d7548190ac15093aa7001db7 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d7336c06308190ac72154134a26842 completed April 9, 2026, 5:04 a.m.
Created at: April 6, 2026, 11:42 a.m.