Triple

T6490382
Position Surface form Disambiguated ID Type / Status
Subject Woodland, Georgia E148019 entity
Predicate hasName P744 FINISHED
Object Woodland
Woodland is a small city located in Talbot County, Georgia, in the United States.
 E596111 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: Woodland | Statement: [Woodland, Georgia, hasName, Woodland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woodland
Context triple: [Woodland, Georgia, hasName, Woodland]
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • C. Woodland
    Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
  • D. Woodlands
    Woodlands is a residential and commercial town in northern Singapore that serves as a key land border crossing point to Malaysia across the Straits of Johor.
  • E. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • 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: Woodland
Triple: [Woodland, Georgia, hasName, Woodland]
Generated description
Woodland is a small city located in Talbot County, Georgia, in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woodland
Target entity description: Woodland is a small city located in Talbot County, Georgia, in the United States.
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • C. Woodland
    Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
  • D. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • E. Woodlands
    Woodlands is a residential and commercial town in northern Singapore that serves as a key land border crossing point to Malaysia across the Straits of Johor.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9a8d8481908d88e5c9f0c773f7 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653bcb63081908be29abd0084d266 completed March 27, 2026, 9:54 a.m.
NEDg Description generation batch_69c6553c17bc81908719ecc7db9e3960 completed March 27, 2026, 10 a.m.
NED2 Entity disambiguation (via description) batch_69c655f4ee5c81909620e732b72ee694 completed March 27, 2026, 10:03 a.m.
Created at: March 22, 2026, 4:53 p.m.