Triple

T3653340
Position Surface form Disambiguated ID Type / Status
Subject Devs E77471 entity
Predicate mainCharacter P1183 FINISHED
Object Forest
Forest is the central protagonist of the game *Devs*, around whom the story’s main events and character dynamics revolve.
 E375722 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: Forest | Statement: [Devs, mainCharacter, Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Forest
Context triple: [Devs, mainCharacter, Forest]
  • 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. 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.
  • D. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • E. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • 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: Forest
Triple: [Devs, mainCharacter, Forest]
Generated description
Forest is the central protagonist of the game *Devs*, around whom the story’s main events and character dynamics revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Forest
Target entity description: Forest is the central protagonist of the game *Devs*, around whom the story’s main events and character dynamics revolve.
  • A. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • B. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • C. 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.
  • D. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • E. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • 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_69ad85def5cc8190863dccf55a18bebb completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3b805a48190a7bc230a382365d6 completed March 8, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f4541dc8190b794eae019dcffbf completed March 13, 2026, 5:54 p.m.
NEDg Description generation batch_69b45258be648190a98f60bd0cf57faa completed March 13, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_69b45eec592481908e2f002aa2127849 completed March 13, 2026, 7:01 p.m.
Created at: March 8, 2026, 3:24 p.m.