Triple

T7755704
Position Surface form Disambiguated ID Type / Status
Subject Stan Laurel E175890 entity
Predicate familyName P18 FINISHED
Object Jefferson
Jefferson is the family name of Stan Laurel, the famed English comic actor and one half of the legendary film duo Laurel and Hardy.
 E689559 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: Jefferson | Statement: [Stan Laurel, familyName, Jefferson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jefferson
Context triple: [Stan Laurel, familyName, Jefferson]
  • A. Jefferson
    Jefferson is a small city in northeastern Georgia that serves as the county seat of Jackson County and lies within the state's historic gold-mining region.
  • B. Jefferson
    Jefferson is a domestic cat known by the given name "Jefferson."
  • C. Jefferson
    Jefferson is the fictional Mississippi town that serves as the central setting in many of William Faulkner’s Yoknapatawpha County stories and novels.
  • D. Jefferson
    Jefferson is a city in Iowa, United States, known as the birthplace of pioneering American pollster George Gallup.
  • E. Jefferson
    Jefferson is the middle name of William Jefferson "Bill" Clinton, the 42nd president of the United States.
  • 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: Jefferson
Triple: [Stan Laurel, familyName, Jefferson]
Generated description
Jefferson is the family name of Stan Laurel, the famed English comic actor and one half of the legendary film duo Laurel and Hardy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jefferson
Target entity description: Jefferson is the family name of Stan Laurel, the famed English comic actor and one half of the legendary film duo Laurel and Hardy.
  • A. Jefferson
    Jefferson is a prominent American surname most famously associated with Thomas Jefferson, the third president of the United States and principal author of the Declaration of Independence.
  • B. Jefferson
    Jefferson is a domestic cat known by the given name "Jefferson."
  • C. Jefferson
    Jefferson is the middle name of William Jefferson "Bill" Clinton, the 42nd president of the United States.
  • D. Jefferson
    Jefferson is a city in Iowa, United States, known as the birthplace of pioneering American pollster George Gallup.
  • E. Jefferson
    Jefferson is the fictional Mississippi town that serves as the central setting in many of William Faulkner’s Yoknapatawpha County stories and novels.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703d9d8fc8190b51faeb081ee425f completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c902b3308c8190ae9a8705087d2e8d completed March 29, 2026, 10:45 a.m.
NEDg Description generation batch_69c902dd915c8190a7059d73428f5cd7 completed March 29, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_69c90348e86c8190b6d61d4a58e79b81 completed March 29, 2026, 10:47 a.m.
Created at: March 27, 2026, 4:08 p.m.