Triple
T3639621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castilla |
E77154
|
entity |
| Predicate | hasSpecies |
P965
|
FINISHED |
| Object |
Castilla ulei
Castilla ulei is a species of tropical tree in the genus Castilla, a group known for latex-producing trees native to Central and South America.
|
E375746
|
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: Castilla ulei | Statement: [Castilla, hasSpecies, Castilla ulei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Castilla ulei Context triple: [Castilla, hasSpecies, Castilla ulei]
-
A.
Manteigas
Manteigas is a small mountain town in central Portugal, known for its scenic location in the Serra da Estrela range and its natural landscapes.
-
B.
Manteca
Manteca is a city in California’s Central Valley known for its agricultural roots, suburban growth, and role as a commuter hub between the Bay Area and inland communities.
-
C.
Granadina
Granadina is the Spanish term used to refer to a female inhabitant or native of the city of Granada in Spain.
-
D.
Serrano
Serrano are an Indigenous people of Southern California traditionally inhabiting the San Bernardino Mountains and surrounding desert regions.
-
E.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
- 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: Castilla ulei Triple: [Castilla, hasSpecies, Castilla ulei]
Generated description
Castilla ulei is a species of tropical tree in the genus Castilla, a group known for latex-producing trees native to Central and South America.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Castilla ulei Target entity description: Castilla ulei is a species of tropical tree in the genus Castilla, a group known for latex-producing trees native to Central and South America.
-
A.
Manteigas
Manteigas is a small mountain town in central Portugal, known for its scenic location in the Serra da Estrela range and its natural landscapes.
-
B.
Manteca
Manteca is a city in California’s Central Valley known for its agricultural roots, suburban growth, and role as a commuter hub between the Bay Area and inland communities.
-
C.
Granadina
Granadina is the Spanish term used to refer to a female inhabitant or native of the city of Granada in Spain.
-
D.
Serrano
Serrano are an Indigenous people of Southern California traditionally inhabiting the San Bernardino Mountains and surrounding desert regions.
-
E.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc32b83188190bfc0ed4dc8f66730 |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f2a8a5c8190b84dcf4b4b8a939e |
completed | March 13, 2026, 5:53 p.m. |
| NEDg | Description generation | batch_69b45292546c81909770dcd6239dbda3 |
completed | March 13, 2026, 6:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b45f76fcc48190bab9bc6ce83700eb |
completed | March 13, 2026, 7:03 p.m. |
Created at: March 8, 2026, 3:24 p.m.