Triple

T23229037
Position Surface form Disambiguated ID Type / Status
Subject Rangers de Talca E581096 entity
Predicate shortName P43 FINISHED
Object Rangers
Rangers is a Chilean professional football club based in the city of Talca.
 E1578869 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: Rangers | Statement: [Rangers de Talca, shortName, Rangers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rangers
Context triple: [Rangers de Talca, shortName, Rangers]
  • A. Rangers
    Rangers are elite U.S. Army light infantry soldiers trained for rapid deployment and specialized combat operations.
  • B. Rangers
    The Rangers are the athletic teams representing the University of Wisconsin–Parkside in collegiate sports.
  • C. Rangers
    Rangers is the short name for the Kitchener Rangers, a major junior ice hockey team in the Ontario Hockey League based in Kitchener, Ontario, Canada.
  • D. Rangers
    Rangers is the nickname of the Royal Ranger Regiment, a distinguished military unit known for its specialized light infantry and reconnaissance capabilities.
  • E. Rangers
    Rangers is a common shortened name for the Pakistan Rangers, a federal paramilitary law enforcement organization responsible for border security and internal security duties in Pakistan.
  • 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: Rangers
Triple: [Rangers de Talca, shortName, Rangers]
Generated description
Rangers is a Chilean professional football club based in the city of Talca.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rangers
Target entity description: Rangers is a Chilean professional football club based in the city of Talca.
  • A. Rangers
    Rangers is a Scottish professional football club based in Glasgow, widely known as one of the most successful and historically significant teams in European football.
  • B. Rangers
    Rangers is the short name for the Kitchener Rangers, a major junior ice hockey team in the Ontario Hockey League based in Kitchener, Ontario, Canada.
  • C. Rangers
    Rangers is the nickname of the Royal Ranger Regiment, a distinguished military unit known for its specialized light infantry and reconnaissance capabilities.
  • D. Rangers
    Rangers is a common shortened name for the Pakistan Rangers, a federal paramilitary law enforcement organization responsible for border security and internal security duties in Pakistan.
  • E. Rangers
    The Rangers are the athletic teams representing the University of Wisconsin–Parkside in collegiate sports.
  • 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_69e246043c48819089bae72c9a9c306c completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f1923131c081909c6e84b1a0c32e0d completed April 29, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c3f55c95081909db75c19bc905c93 completed May 19, 2026, 10:45 a.m.
NEDg Description generation batch_6a0c4028b44c8190bde6e2c76b5f1587 completed May 19, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0c4367753c8190a4f6dbf2afd12b76 completed May 19, 2026, 11:03 a.m.
Created at: April 17, 2026, 4:09 p.m.