Triple

T18062073
Position Surface form Disambiguated ID Type / Status
Subject Vatican walls E432198 entity
Predicate hasPart P35 FINISHED
Object Bastione di San Carlo
Bastione di San Carlo is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
 E1320814 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: Bastione di San Carlo | Statement: [Vatican walls, hasPart, Bastione di San Carlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bastione di San Carlo
Context triple: [Vatican walls, hasPart, Bastione di San Carlo]
  • A. Bastione di San Lorenzo
    Bastione di San Lorenzo is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
  • B. Bastione di San Giovanni
    Bastione di San Giovanni is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
  • C. Bastione di San Tommaso
    Bastione di San Tommaso is a historic defensive bastion incorporated into the fortification system surrounding Vatican City.
  • D. Bastione di San Matteo
    Bastione di San Matteo is a defensive bastion incorporated into the historic fortification system of the Vatican City walls.
  • E. Bastione di San Paolo
    Bastione di San Paolo is a historic defensive bastion incorporated into the fortification system surrounding Vatican City.
  • 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: Bastione di San Carlo
Triple: [Vatican walls, hasPart, Bastione di San Carlo]
Generated description
Bastione di San Carlo is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bastione di San Carlo
Target entity description: Bastione di San Carlo is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
  • A. Bastione di San Lorenzo
    Bastione di San Lorenzo is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
  • B. Bastione di San Giovanni
    Bastione di San Giovanni is a historic defensive bastion incorporated into the fortification system of the Vatican City walls.
  • C. Bastione di San Tommaso
    Bastione di San Tommaso is a historic defensive bastion incorporated into the fortification system surrounding Vatican City.
  • D. Bastione di San Matteo
    Bastione di San Matteo is a defensive bastion incorporated into the historic fortification system of the Vatican City walls.
  • E. Bastione di San Paolo
    Bastione di San Paolo is a historic defensive bastion incorporated into the fortification system surrounding Vatican City.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c107351c8190a2bfdb46754c2c6e completed April 19, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a03d7600a988190a3f4fb60ee469423 completed May 13, 2026, 1:44 a.m.
NEDg Description generation batch_6a03d8512d4c8190b113f7ed1f8a044c completed May 13, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_6a03d8d863cc819098b46d5d26db05cd completed May 13, 2026, 1:50 a.m.
Created at: April 10, 2026, 10:26 a.m.