Triple

T2720363
Position Surface form Disambiguated ID Type / Status
Subject State of São Paulo E60066 entity
Predicate hasCity P316 FINISHED
Object Diadema
Diadema is an industrial and densely populated municipality in the Greater São Paulo metropolitan area of southeastern Brazil.
 E293504 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: Diadema | Statement: [State of São Paulo, hasCity, Diadema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Diadema
Context triple: [State of São Paulo, hasCity, Diadema]
  • A. Arrecife
    Arrecife is the capital and main port city of the Spanish island of Lanzarote in the Canary Islands, known for its coastal promenades and volcanic island surroundings.
  • B. Culebrita
    Culebrita is a small, uninhabited cay off the coast of Culebra, Puerto Rico, known for its pristine beaches, clear waters, and historic lighthouse.
  • C. Gorgonia
    Gorgonia was a pious Christian woman of the 4th century, venerated as a saint and known primarily as the devout sister of Gregory of Nazianzus.
  • D. Tayassu
    Tayassu is a genus of New World peccaries, medium-sized pig-like mammals native to Central and South American forests and scrublands.
  • E. Guane
    Guane is a small town and municipality in western Cuba known for its rural character and tobacco-growing traditions.
  • 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: Diadema
Triple: [State of São Paulo, hasCity, Diadema]
Generated description
Diadema is an industrial and densely populated municipality in the Greater São Paulo metropolitan area of southeastern Brazil.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Diadema
Target entity description: Diadema is an industrial and densely populated municipality in the Greater São Paulo metropolitan area of southeastern Brazil.
  • A. Arrecife
    Arrecife is the capital and main port city of the Spanish island of Lanzarote in the Canary Islands, known for its coastal promenades and volcanic island surroundings.
  • B. Culebrita
    Culebrita is a small, uninhabited cay off the coast of Culebra, Puerto Rico, known for its pristine beaches, clear waters, and historic lighthouse.
  • C. Gorgonia
    Gorgonia was a pious Christian woman of the 4th century, venerated as a saint and known primarily as the devout sister of Gregory of Nazianzus.
  • D. Tayassu
    Tayassu is a genus of New World peccaries, medium-sized pig-like mammals native to Central and South American forests and scrublands.
  • E. Guane
    Guane is a small town and municipality in western Cuba known for its rural character and tobacco-growing traditions.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdab06d388190acf690787fe58ab5 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6914f70819099482893d026f34b completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb726182081909570e4cb7a364e4d completed March 10, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69afb78f9d08819087d6f31fe1e4e61c completed March 10, 2026, 6:17 a.m.
Created at: March 6, 2026, 9:55 p.m.