Triple
T3599022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro Vicuña Mackenna |
E76209
|
entity |
| Predicate | hasNamePart |
P5298
|
FINISHED |
| Object |
Cerro
Cerro is a Spanish term commonly used in place names throughout Latin America to denote a hill or mountain.
|
E373652
|
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: Cerro | Statement: [Cerro Vicuña Mackenna, hasNamePart, Cerro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cerro Context triple: [Cerro Vicuña Mackenna, hasNamePart, Cerro]
-
A.
Cerro Baúl
Cerro Baúl is a prominent flat-topped mountain in southern Peru that served as a key administrative and ceremonial center of the Wari civilization.
-
B.
Cerro Jefe
Cerro Jefe is a prominent mountain in central Panama known for its cloud forests, biodiversity, and panoramic views over the surrounding isthmus.
-
C.
Cerro Hudson
Cerro Hudson is a large, glacier-covered stratovolcano in southern Chile known for its highly explosive eruptions and significant impact on regional climate and landscapes.
-
D.
Cerro San Rafael
Cerro San Rafael is a prominent mountain peak in northeastern Mexico, notable for being the highest summit in the Sierra Madre Oriental range.
-
E.
Cerro Otto
Cerro Otto is a scenic mountain in Argentina’s Patagonia region, popular for its panoramic views over Bariloche and its accessible hiking and cable car routes.
- 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: Cerro Triple: [Cerro Vicuña Mackenna, hasNamePart, Cerro]
Generated description
Cerro is a Spanish term commonly used in place names throughout Latin America to denote a hill or mountain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cerro Target entity description: Cerro is a Spanish term commonly used in place names throughout Latin America to denote a hill or mountain.
-
A.
Cerro Baúl
Cerro Baúl is a prominent flat-topped mountain in southern Peru that served as a key administrative and ceremonial center of the Wari civilization.
-
B.
Cerro Jefe
Cerro Jefe is a prominent mountain in central Panama known for its cloud forests, biodiversity, and panoramic views over the surrounding isthmus.
-
C.
Cerro Hudson
Cerro Hudson is a large, glacier-covered stratovolcano in southern Chile known for its highly explosive eruptions and significant impact on regional climate and landscapes.
-
D.
Cerro San Rafael
Cerro San Rafael is a prominent mountain peak in northeastern Mexico, notable for being the highest summit in the Sierra Madre Oriental range.
-
E.
Cerro Otto
Cerro Otto is a scenic mountain in Argentina’s Patagonia region, popular for its panoramic views over Bariloche and its accessible hiking and cable car routes.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc19e9e98819094455cb3c4efcb9a |
completed | March 8, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b43309a9b48190bc2aa6f970d45612 |
completed | March 13, 2026, 3:53 p.m. |
| NEDg | Description generation | batch_69b43705642881909c62b7363a4f3a12 |
completed | March 13, 2026, 4:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4379cd04c81909246747bcc357261 |
completed | March 13, 2026, 4:13 p.m. |
Created at: March 8, 2026, 3:22 p.m.