Triple
T17480795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maldonado Department |
E425652
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Aiguá
Aiguá is a small town in southeastern Uruguay known for its rural character and location within the Maldonado Department.
|
E1272814
|
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: Aiguá | Statement: [Maldonado Department, hasCity, Aiguá]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aiguá Context triple: [Maldonado Department, hasCity, Aiguá]
-
A.
Villaguay
Villaguay is a city in central Argentina known as an important agricultural and commercial hub within Entre Ríos Province.
-
B.
Río Turbio
Río Turbio is a coal-mining town in southern Patagonia, Argentina, known for its significant lignite deposits and harsh, windy climate.
-
C.
Yaguará
Yaguará is a municipality and town in the Huila Department of southwestern Colombia, known for its proximity to the Betania Reservoir and its agricultural activities.
-
D.
Gualeguay
Gualeguay is a city in eastern Argentina known for its agricultural economy and location along the Gualeguay River in Entre Ríos Province.
-
E.
Río Rocha
Río Rocha is a river in central Bolivia that flows through the city of Cochabamba and plays a key role in the region’s drainage and environmental conditions.
- 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: Aiguá Triple: [Maldonado Department, hasCity, Aiguá]
Generated description
Aiguá is a small town in southeastern Uruguay known for its rural character and location within the Maldonado Department.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aiguá Target entity description: Aiguá is a small town in southeastern Uruguay known for its rural character and location within the Maldonado Department.
-
A.
Villaguay
Villaguay is a city in central Argentina known as an important agricultural and commercial hub within Entre Ríos Province.
-
B.
Río Turbio
Río Turbio is a coal-mining town in southern Patagonia, Argentina, known for its significant lignite deposits and harsh, windy climate.
-
C.
Yaguará
Yaguará is a municipality and town in the Huila Department of southwestern Colombia, known for its proximity to the Betania Reservoir and its agricultural activities.
-
D.
Gualeguay
Gualeguay is a city in eastern Argentina known for its agricultural economy and location along the Gualeguay River in Entre Ríos Province.
-
E.
Río Rocha
Río Rocha is a river in central Bolivia that flows through the city of Cochabamba and plays a key role in the region’s drainage and environmental conditions.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bfd75481908c20bc2c1cbff593 |
completed | April 19, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c1faa20c8190910d429fbca4e6cb |
completed | May 11, 2026, 11:48 a.m. |
| NEDg | Description generation | batch_6a01c6373f008190864593e8f582b707 |
completed | May 11, 2026, 12:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01c6d4313c819086b40432c738efcb |
completed | May 11, 2026, 12:08 p.m. |
Created at: April 10, 2026, 5:48 a.m.