Triple
T16535564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mendoza River |
E401680
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Río Blanco
Río Blanco is a mountain river in Argentina’s Mendoza province that contributes glacial and snowmelt waters to the Mendoza River system.
|
E1217849
|
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: Río Blanco | Statement: [Mendoza River, hasTributary, Río Blanco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Río Blanco Context triple: [Mendoza River, hasTributary, Río Blanco]
-
A.
Río Blanco
Río Blanco is a municipality and industrial town in the Mexican state of Veracruz, historically known for its textile industry and role in early 20th-century labor movements.
-
B.
Río Blanco
Río Blanco is a river in Colombia associated with the municipality of Choachí in the Andean region.
-
C.
Huerfano River
The Huerfano River is a tributary of the Arkansas River in southern Colorado, known for flowing through Huerfano County and lending its name to the region.
-
D.
Río Frío
Río Frío is a river in Colombia associated with the municipality of Piedecuesta in the Santander Department.
-
E.
Río Frío
Río Frío is a bus rapid transit station on Line 2 of the Metrobús system in Mexico City.
- 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: Río Blanco Triple: [Mendoza River, hasTributary, Río Blanco]
Generated description
Río Blanco is a mountain river in Argentina’s Mendoza province that contributes glacial and snowmelt waters to the Mendoza River system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Río Blanco Target entity description: Río Blanco is a mountain river in Argentina’s Mendoza province that contributes glacial and snowmelt waters to the Mendoza River system.
-
A.
Río Blanco
Río Blanco is a municipality and industrial town in the Mexican state of Veracruz, historically known for its textile industry and role in early 20th-century labor movements.
-
B.
Río Blanco
Río Blanco is a river in Colombia associated with the municipality of Choachí in the Andean region.
-
C.
Huerfano River
The Huerfano River is a tributary of the Arkansas River in southern Colorado, known for flowing through Huerfano County and lending its name to the region.
-
D.
Río Frío
Río Frío is a river in Colombia associated with the municipality of Piedecuesta in the Santander Department.
-
E.
Río Frío
Río Frío is a bus rapid transit station on Line 2 of the Metrobús system in Mexico City.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e345574d88819094548367bf983078 |
completed | April 18, 2026, 8:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006094dee481908757b84c10d0dc19 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a0060eca9fc81908f376cd2f7219bcd |
completed | May 10, 2026, 10:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00622f44ec8190a7d66c7882ae28b2 |
completed | May 10, 2026, 10:47 a.m. |
Created at: April 10, 2026, 5:15 a.m.