Triple

T3290372
Position Surface form Disambiguated ID Type / Status
Subject Jackson Rathbone E69085 entity
Predicate givenName P17 FINISHED
Object Monroe
Monroe is a given name used as a first name, notably borne by actor Jackson Rathbone.
 E343738 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: Monroe | Statement: [Jackson Rathbone, givenName, Monroe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monroe
Context triple: [Jackson Rathbone, givenName, Monroe]
  • A. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • B. Monroe
    Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • C. Monroe
    Monroe is a city in southeastern Michigan known for its location along the River Raisin and its historical significance in the War of 1812.
  • D. Monroe
    Monroe is a small city in North Carolina that serves as part of the greater Charlotte metropolitan area.
  • E. Monroe
    Monroe is a mid-sized city in northeastern Louisiana known as a regional hub for commerce, education, and culture along the Ouachita River.
  • 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: Monroe
Triple: [Jackson Rathbone, givenName, Monroe]
Generated description
Monroe is a given name used as a first name, notably borne by actor Jackson Rathbone.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monroe
Target entity description: Monroe is a given name used as a first name, notably borne by actor Jackson Rathbone.
  • A. Monroe
    Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • B. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • C. Monroe
    Monroe is a small city in North Carolina that serves as part of the greater Charlotte metropolitan area.
  • D. Monroe
    Monroe is a mid-sized city in northeastern Louisiana known as a regional hub for commerce, education, and culture along the Ouachita River.
  • E. Monroe
    Monroe is a city in southeastern Michigan known for its location along the River Raisin and its historical significance in the War of 1812.
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb05bd6b08190bcb9f0e5da82bc21 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e862835881909c2f3b8f86f10742 completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8f6a7c48190bc457f348c3a7179 completed March 12, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_69b2e986dcc88190bd3daa6c6fdcb50e completed March 12, 2026, 4:27 p.m.
Created at: March 8, 2026, 3:10 p.m.