Triple

T5829129
Position Surface form Disambiguated ID Type / Status
Subject Nancy Sinatra E129301 entity
Predicate notableWork P4 FINISHED
Object Sugar Town
"Sugar Town" is a 1966 pop song by Nancy Sinatra, known for its light, whimsical style and catchy, laid-back melody.
 E548804 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: Sugar Town | Statement: [Nancy Sinatra, notableWork, Sugar Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sugar Town
Context triple: [Nancy Sinatra, notableWork, Sugar Town]
  • A. Red Town
    Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
  • B. Mob Town
    Mob Town is a historic nickname for the city of Baltimore, reflecting its long-standing reputation for civil unrest and rowdy public gatherings in the 19th century.
  • C. Stone City
    Stone City is an ancient walled city and historic fortification area that forms part of the old core of Nanjing, China.
  • D. Her Town Too
    "Her Town Too" is a 1981 soft rock song by James Taylor (with J.D. Souther) known for its reflective lyrics about the emotional fallout of a breakup.
  • E. My Kind of Town
    "My Kind of Town" is a popular American song, famously performed by Frank Sinatra, that celebrates the city of Chicago and has become a classic of the Great American Songbook.
  • 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: Sugar Town
Triple: [Nancy Sinatra, notableWork, Sugar Town]
Generated description
"Sugar Town" is a 1966 pop song by Nancy Sinatra, known for its light, whimsical style and catchy, laid-back melody.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sugar Town
Target entity description: "Sugar Town" is a 1966 pop song by Nancy Sinatra, known for its light, whimsical style and catchy, laid-back melody.
  • A. Red Town
    Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
  • B. Mob Town
    Mob Town is a historic nickname for the city of Baltimore, reflecting its long-standing reputation for civil unrest and rowdy public gatherings in the 19th century.
  • C. Stone City
    Stone City is an ancient walled city and historic fortification area that forms part of the old core of Nanjing, China.
  • D. Her Town Too
    "Her Town Too" is a 1981 soft rock song by James Taylor (with J.D. Souther) known for its reflective lyrics about the emotional fallout of a breakup.
  • E. My Kind of Town
    "My Kind of Town" is a popular American song, famously performed by Frank Sinatra, that celebrates the city of Chicago and has become a classic of the Great American Songbook.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03467dfe48190b51757b33681bc20 completed March 22, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09863be3c8190bba357bf64e22917 completed March 23, 2026, 1:33 a.m.
NEDg Description generation batch_69c098d936d081909d930fc8b6b3fd67 completed March 23, 2026, 1:35 a.m.
NED2 Entity disambiguation (via description) batch_69c09947c5fc8190ba279ed0f991f9a9 completed March 23, 2026, 1:37 a.m.
Created at: March 22, 2026, 3:54 p.m.