Triple

T8655826
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan City of Florence E205412 entity
Predicate contains P35 FINISHED
Object Signa
Signa is a historic Tuscan town near Florence, Italy, known for its traditional straw weaving and picturesque setting along the Arno River.
 E748681 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: Signa | Statement: [Metropolitan City of Florence, contains, Signa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Signa
Context triple: [Metropolitan City of Florence, contains, Signa]
  • A. Sidonia
    Sidonia is a brilliant, enigmatic Jewish financier and philosopher in Benjamin Disraeli’s novel "Coningsby, or The New Generation," often seen as a reflection of Disraeli’s views on power, politics, and Jewish identity.
  • B. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • C. Kadina
    Kadina is a historic copper mining town and one of the main commercial centers on South Australia's Yorke Peninsula.
  • D. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • E. Derisha
    Derisha is a lexical form or word used in a linguistic context, likely representing one member of a pair of related terms alongside Perisha.
  • 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: Signa
Triple: [Metropolitan City of Florence, contains, Signa]
Generated description
Signa is a historic Tuscan town near Florence, Italy, known for its traditional straw weaving and picturesque setting along the Arno River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Signa
Target entity description: Signa is a historic Tuscan town near Florence, Italy, known for its traditional straw weaving and picturesque setting along the Arno River.
  • A. Sidonia
    Sidonia is a brilliant, enigmatic Jewish financier and philosopher in Benjamin Disraeli’s novel "Coningsby, or The New Generation," often seen as a reflection of Disraeli’s views on power, politics, and Jewish identity.
  • B. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • C. Kadina
    Kadina is a historic copper mining town and one of the main commercial centers on South Australia's Yorke Peninsula.
  • D. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • E. Derisha
    Derisha is a lexical form or word used in a linguistic context, likely representing one member of a pair of related terms alongside Perisha.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4844586081909b687e278496eefa completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecce40c248190b4f2b21a1ecde80b completed April 2, 2026, 8:09 p.m.
NEDg Description generation batch_69cece8c4bdc8190988990c675f50f86 completed April 2, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_69cecf3a0e78819082cc7c43eceae309 completed April 2, 2026, 8:19 p.m.
Created at: March 30, 2026, 6:29 p.m.