Triple

T1986998
Position Surface form Disambiguated ID Type / Status
Subject Canino E43163 entity
Predicate locatedNear P294 FINISHED
Object Cellere
Cellere is a small town in the Lazio region of central Italy, known for its rural landscape and proximity to other historic villages such as Canino.
 E223010 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: Cellere | Statement: [Canino, locatedNear, Cellere]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cellere
Context triple: [Canino, locatedNear, Cellere]
  • A. Colwell
    Colwell is a surname most notably associated with Rita R. Colwell, an influential American microbiologist and former director of the U.S. National Science Foundation.
  • B. Cellese
    Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
  • C. Zyvex
    Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
  • D. Setonix
    Setonix is a genus of small marsupials best known for including the quokka, a short-tailed wallaby native to southwestern Australia.
  • E. Immunix
    Immunix was a security-focused software company known for developing Linux security technologies, including the precursor to the AppArmor mandatory access control system.
  • 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: Cellere
Triple: [Canino, locatedNear, Cellere]
Generated description
Cellere is a small town in the Lazio region of central Italy, known for its rural landscape and proximity to other historic villages such as Canino.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cellere
Target entity description: Cellere is a small town in the Lazio region of central Italy, known for its rural landscape and proximity to other historic villages such as Canino.
  • A. Colwell
    Colwell is a surname most notably associated with Rita R. Colwell, an influential American microbiologist and former director of the U.S. National Science Foundation.
  • B. Cellese
    Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
  • C. Zyvex
    Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
  • D. Setonix
    Setonix is a genus of small marsupials best known for including the quokka, a short-tailed wallaby native to southwestern Australia.
  • E. Immunix
    Immunix was a security-focused software company known for developing Linux security technologies, including the precursor to the AppArmor mandatory access control system.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb840a5708190a9b64564b855fb22 completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae033410a88190bac79032a012549a completed March 8, 2026, 11:16 p.m.
NEDg Description generation batch_69ae03e575a88190a93181eb9d9bc3eb completed March 8, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69ae0473aecc8190b3da07fb8fd18e81 completed March 8, 2026, 11:21 p.m.
Created at: March 4, 2026, 7:37 p.m.