Triple
T36874282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | northern Patagonian Andes |
E911301
|
entity |
| Predicate | ecosystem |
P964
|
FINISHED |
| Object |
Andean-Patagonian forests
The Andean-Patagonian forests are temperate, biodiversity-rich woodlands of southern South America, dominated by Nothofagus and other native tree species and shaped by a cool, wet climate along the Andean range.
|
E133822
|
NE FINISHED |
How this triple was built (2 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: Andean-Patagonian forests | Statement: [northern Patagonian Andes, ecosystem, Andean-Patagonian forests]
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: Andean-Patagonian forests Triple: [northern Patagonian Andes, ecosystem, Andean-Patagonian forests]
Generated description
The Andean-Patagonian forests are temperate, biodiversity-rich woodlands of southern South America, dominated by Nothofagus and other native tree species and shaped by a cool, wet climate along the Andean range.
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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cff599408190afda2781c11e176e |
completed | May 3, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e161dbf74819083712e5038938e3b |
completed | June 26, 2026, 6:03 a.m. |
| NEDg | Description generation | batch_6a3e16c7ae008190aed858fd5da64a5d |
completed | June 26, 2026, 6:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3e2225d4fc8190baaf1e61f7e1642f |
completed | June 26, 2026, 6:54 a.m. |
Created at: May 3, 2026, 4:13 p.m.