Triple
T17325451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tandil |
E420674
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Lago del Fuerte |
—
|
NE ONDG |
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: Lago del Fuerte | Statement: [Tandil, hasAttraction, Lago del Fuerte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lago del Fuerte Context triple: [Tandil, hasAttraction, Lago del Fuerte]
-
A.
Lago Dorado
Lago Dorado is the central lake around which Disney’s Coronado Springs Resort is built, serving as a scenic focal point for the property.
-
B.
Lake Lucero
Lake Lucero is a seasonal, gypsum-rich playa lake in New Mexico whose evaporating waters help form the brilliant white sand dunes of White Sands National Park.
-
C.
Fúquene Lake
Fúquene Lake is a high-altitude Andean lake in central Colombia known for its ecological importance and surrounding agricultural landscapes.
-
D.
Lake Del Valle
Lake Del Valle is a man-made reservoir in Alameda County, California, primarily used for water storage, recreation, and as part of the state's water conveyance system.
-
E.
Conguillío Lake
Conguillío Lake is a scenic glacial lake in Chile’s Conguillío National Park, renowned for its clear waters, surrounding Araucaria forests, and dramatic views of the nearby Llaima Volcano.
- 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: Lago del Fuerte Triple: [Tandil, hasAttraction, Lago del Fuerte]
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lago del Fuerte Target entity description: Lago del Fuerte is an artificial lake and popular recreational spot in Tandil, Argentina, known for its scenic views, outdoor activities, and surrounding green spaces.
-
A.
Lago Dorado
Lago Dorado is the central lake around which Disney’s Coronado Springs Resort is built, serving as a scenic focal point for the property.
-
B.
Lake Lucero
Lake Lucero is a seasonal, gypsum-rich playa lake in New Mexico whose evaporating waters help form the brilliant white sand dunes of White Sands National Park.
-
C.
Fúquene Lake
Fúquene Lake is a high-altitude Andean lake in central Colombia known for its ecological importance and surrounding agricultural landscapes.
-
D.
Lake Del Valle
Lake Del Valle is a man-made reservoir in Alameda County, California, primarily used for water storage, recreation, and as part of the state's water conveyance system.
-
E.
Conguillío Lake
Conguillío Lake is a scenic glacial lake in Chile’s Conguillío National Park, renowned for its clear waters, surrounding Araucaria forests, and dramatic views of the nearby Llaima Volcano.
- F. None of above. chosen
Provenance (4 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d24e548190a766dd246a4d63d4 |
completed | April 19, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01954ecadc8190a6484ff0a207fe9b |
completed | May 11, 2026, 8:37 a.m. |
| NEDg | Description generation | batch_6a01964923248190b0c3548d90bc1dd9 |
in_progress | May 11, 2026, 8:41 a.m. |
Created at: April 10, 2026, 5:43 a.m.