Triple
T20379487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassia |
E497783
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object |
Cássia
Cássia is a given name commonly used in Portuguese-speaking countries, often associated with women and derived from the Latin name Cassia.
|
E1426567
|
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: Cássia | Statement: [Cassia, relatedName, Cássia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cássia Context triple: [Cassia, relatedName, Cássia]
-
A.
Cleuza
Cleuza is a central character in the Brazilian film "Linha de Passe," portrayed as a struggling single mother raising her sons in the outskirts of São Paulo.
-
B.
Carriço
Carriço is a civil parish within the municipality of Pombal in central Portugal, known for its rural character and local community life.
-
C.
Conceição
Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
-
D.
Itabaiana
Itabaiana is a prominent inland city in the Brazilian state of Sergipe, known for its vibrant commerce, agricultural production, and strategic location as a regional hub.
-
E.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
- 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: Cássia Triple: [Cassia, relatedName, Cássia]
Generated description
Cássia is a given name commonly used in Portuguese-speaking countries, often associated with women and derived from the Latin name Cassia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cássia Target entity description: Cássia is a given name commonly used in Portuguese-speaking countries, often associated with women and derived from the Latin name Cassia.
-
A.
Cleuza
Cleuza is a central character in the Brazilian film "Linha de Passe," portrayed as a struggling single mother raising her sons in the outskirts of São Paulo.
-
B.
Carriço
Carriço is a civil parish within the municipality of Pombal in central Portugal, known for its rural character and local community life.
-
C.
Conceição
Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
-
D.
Itabaiana
Itabaiana is a prominent inland city in the Brazilian state of Sergipe, known for its vibrant commerce, agricultural production, and strategic location as a regional hub.
-
E.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678af651c8190b4922294a937e699 |
completed | April 20, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a087095286c8190afdcb855220526fc |
completed | May 16, 2026, 1:26 p.m. |
| NEDg | Description generation | batch_6a087129ce3c8190a67ac34ec697ad31 |
completed | May 16, 2026, 1:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0871e3573c81908216b5e508374081 |
completed | May 16, 2026, 1:32 p.m. |
Created at: April 16, 2026, 11:27 a.m.