Triple

T5592657
Position Surface form Disambiguated ID Type / Status
Subject Sevel Sud plant, Atessa, Italy E146917 entity
Predicate locatedIn P40 FINISHED
Object Atessa
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
E533207 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: Atessa | Statement: [Sevel Sud plant, Atessa, Italy, locatedIn, Atessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atessa
Context triple: [Sevel Sud plant, Atessa, Italy, locatedIn, Atessa]
  • A. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • B. Ashti
    Ashti is a town in the Wardha district of Maharashtra, India, known primarily as a local administrative and agricultural center.
  • C. Ateso
    Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Telesia
    Telesia was an important ancient town in the region of Samnium in south-central Italy, known for its strategic and military significance in pre-Roman and Roman times.
  • 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: Atessa
Triple: [Sevel Sud plant, Atessa, Italy, locatedIn, Atessa]
Generated description
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Atessa
Target entity description: Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
  • A. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • B. Ashti
    Ashti is a town in the Wardha district of Maharashtra, India, known primarily as a local administrative and agricultural center.
  • C. Ateso
    Ateso is a Nilotic language spoken primarily by the Teso people of eastern Uganda and western Kenya.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Telesia
    Telesia was an important ancient town in the region of Samnium in south-central Italy, known for its strategic and military significance in pre-Roman and Roman times.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020bb08648190ab1f66cc3e897e6d completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0286b4d2c8190a3224f3082316dc8 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c0372e86c08190bf586256cab23d22 completed March 22, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69c038e5dccc8190a5e1ec45712c00a3 completed March 22, 2026, 6:45 p.m.
Created at: March 22, 2026, 3:38 p.m.