Triple

T15207099
Position Surface form Disambiguated ID Type / Status
Subject Battle of Sanluri E363416 entity
Predicate location P40 FINISHED
Object Sanluri
Sanluri is a historic town in southern Sardinia, Italy, known for its medieval heritage and as the site of a major 1409 battle between Aragonese and Sardinian forces.
E1143080 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: Sanluri | Statement: [Battle of Sanluri, location, Sanluri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanluri
Context triple: [Battle of Sanluri, location, Sanluri]
  • A. Gisondo
    Gisondo is an Italian-origin surname most notably borne by American actor Skyler Gisondo.
  • B. Santena
    Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
  • C. Gualba
    Gualba is a small municipality in the Vallès Oriental comarca of Catalonia, Spain, known for its natural surroundings near the Montseny Massif.
  • D. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • E. Arganil
    Arganil is a municipality and town in central Portugal known for its mountainous landscapes, river beaches, and traditional schist villages.
  • 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: Sanluri
Triple: [Battle of Sanluri, location, Sanluri]
Generated description
Sanluri is a historic town in southern Sardinia, Italy, known for its medieval heritage and as the site of a major 1409 battle between Aragonese and Sardinian forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sanluri
Target entity description: Sanluri is a historic town in southern Sardinia, Italy, known for its medieval heritage and as the site of a major 1409 battle between Aragonese and Sardinian forces.
  • A. Gisondo
    Gisondo is an Italian-origin surname most notably borne by American actor Skyler Gisondo.
  • B. Santena
    Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
  • C. Gualba
    Gualba is a small municipality in the Vallès Oriental comarca of Catalonia, Spain, known for its natural surroundings near the Montseny Massif.
  • D. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • E. Arganil
    Arganil is a municipality and town in central Portugal known for its mountainous landscapes, river beaches, and traditional schist villages.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b8e2788190bd1831762e4181ae completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed33dbda08190a10ba81082d0d183 completed May 9, 2026, 6:25 a.m.
NEDg Description generation batch_69fed47c88d08190a4396b955c9bb388 completed May 9, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69fed50956408190b1426d578803974e completed May 9, 2026, 6:32 a.m.
Created at: April 10, 2026, 3:11 a.m.