Triple
T2720392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of São Paulo |
E60066
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Assis
Assis is a municipality in the western part of the state of São Paulo, Brazil, known as a regional commercial and educational center.
|
E293516
|
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: Assis | Statement: [State of São Paulo, hasCity, Assis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Assis Context triple: [State of São Paulo, hasCity, Assis]
-
A.
Azevêdo
Azevêdo is a Portuguese-language surname commonly found in Brazil and Portugal, associated with several notable public figures.
-
B.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
C.
Moraes Zogoiby
Moraes Zogoiby is the physically deformed, fast-aging narrator and protagonist of Salman Rushdie’s novel "The Moor’s Last Sigh," whose life story reflects the tumultuous history and cultural hybridity of modern India.
-
D.
Paulo
Paulo is the central character in Paulo Coelho’s novel "The Valkyries," whose spiritual journey through the Mojave Desert explores themes of faith, love, and self-discovery.
-
E.
Guilherme
Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
- 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: Assis Triple: [State of São Paulo, hasCity, Assis]
Generated description
Assis is a municipality in the western part of the state of São Paulo, Brazil, known as a regional commercial and educational center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Assis Target entity description: Assis is a municipality in the western part of the state of São Paulo, Brazil, known as a regional commercial and educational center.
-
A.
Azevêdo
Azevêdo is a Portuguese-language surname commonly found in Brazil and Portugal, associated with several notable public figures.
-
B.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
C.
Moraes Zogoiby
Moraes Zogoiby is the physically deformed, fast-aging narrator and protagonist of Salman Rushdie’s novel "The Moor’s Last Sigh," whose life story reflects the tumultuous history and cultural hybridity of modern India.
-
D.
Paulo
Paulo is the central character in Paulo Coelho’s novel "The Valkyries," whose spiritual journey through the Mojave Desert explores themes of faith, love, and self-discovery.
-
E.
Guilherme
Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
- 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.