Triple

T9173548
Position Surface form Disambiguated ID Type / Status
Subject College of Health Sciences (University of Louisiana at Monroe) E220138 entity
Predicate city P40 FINISHED
Object Monroe
Monroe is a city in northeastern Louisiana known as a regional hub for education, healthcare, and commerce along the Ouachita River.
E180923 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: [College of Health Sciences (University of Louisiana at Monroe), city, Monroe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monroe
Context triple: [College of Health Sciences (University of Louisiana at Monroe), city, Monroe]
  • A. 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.
  • 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 surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • 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 given name used as a first name, notably borne by actor Jackson Rathbone.
  • 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: [College of Health Sciences (University of Louisiana at Monroe), city, Monroe]
Generated description
Monroe is a city in northeastern Louisiana known as a regional hub for education, healthcare, and commerce along the Ouachita River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Monroe
Target entity description: Monroe is a city in northeastern Louisiana known as a regional hub for education, healthcare, and commerce along the Ouachita River.
  • A. Monroe chosen
    Monroe is a mid-sized city in northeastern Louisiana known as a regional hub for commerce, education, and culture along the Ouachita River.
  • B. 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.
  • 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 small city in Washington State known for its location in the Skykomish River Valley and its role as a regional hub for outdoor recreation and community events.
  • E. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop, serving the CTA Blue Line.
  • F. None of above.

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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa128d48190b54b8f95d77d81cc completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054a36ef881908079558050c67e7c completed April 4, 2026, midnight
NEDg Description generation batch_69d05597d00c8190bdf51a53497c8042 completed April 4, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_69d056619c988190a11b7eb4a31f93b2 completed April 4, 2026, 12:08 a.m.
Created at: March 30, 2026, 7:22 p.m.