Triple
T5327498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sudbury District |
E123220
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object |
Espanola
Espanola is a small town in Northern Ontario, Canada, known historically for its pulp and paper industry and its location near the North Channel of Lake Huron.
|
E512789
|
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: Espanola | Statement: [Sudbury District, hasAdministrativeCenter, Espanola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espanola Context triple: [Sudbury District, hasAdministrativeCenter, Espanola]
-
A.
Espanola
Española is a small city in northern New Mexico known for its location in the Rio Grande Valley and its blend of Hispanic and Native American cultural heritage.
-
B.
Tasqueña
Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
-
C.
Tagüeña
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
-
D.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
E.
Espinosa
Espinosa is a neighborhood (barrio) within the municipality of Dorado in Puerto Rico.
- 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: Espanola Triple: [Sudbury District, hasAdministrativeCenter, Espanola]
Generated description
Espanola is a small town in Northern Ontario, Canada, known historically for its pulp and paper industry and its location near the North Channel of Lake Huron.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Espanola Target entity description: Espanola is a small town in Northern Ontario, Canada, known historically for its pulp and paper industry and its location near the North Channel of Lake Huron.
-
A.
Espanola
Española is a small city in northern New Mexico known for its location in the Rio Grande Valley and its blend of Hispanic and Native American cultural heritage.
-
B.
Tasqueña
Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
-
C.
Tagüeña
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
-
D.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
E.
Espinosa
Espinosa is a neighborhood (barrio) within the municipality of Dorado in Puerto Rico.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85926c388190a495835caf927624 |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18b00f9c8190b3882f6112546b4a |
completed | March 21, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69bf194c53a48190b0895bbe9aa2f6f1 |
completed | March 21, 2026, 10:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf1a198418819089b25102733f9191 |
completed | March 21, 2026, 10:22 p.m. |
Created at: March 20, 2026, 2 p.m.