Triple
T817976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Americas |
E17691
|
entity |
| Predicate | containsSubregion |
P285
|
FINISHED |
| Object | Pampas |
E25063
|
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: Pampas | Statement: [Americas, containsSubregion, Pampas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pampas Context triple: [Americas, containsSubregion, Pampas]
-
A.
Pampas
chosen
The Pampas is a vast fertile lowland plain in South America, primarily in Argentina, known for its grasslands, agriculture, and cattle ranching.
-
B.
Pampa
Pampa was a pioneering 10th-century Kannada poet, celebrated as one of the “three gems” of classical Kannada literature and best known for his epic works like the Adipurana and Vikramarjuna Vijaya.
-
C.
Pantanal
The Pantanal is one of the world’s largest tropical wetlands, renowned for its extraordinary biodiversity and vast seasonally flooded plains in central South America.
-
D.
Patagonia
Patagonia is a sparsely populated region at the southern end of South America, renowned for its dramatic mountains, glaciers, and windswept plains shared by Chile and Argentina.
-
E.
La Plata Basin
The La Plata Basin is one of South America's largest river basins, encompassing parts of several countries and draining into the Río de la Plata estuary on the Atlantic coast.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab63f4a48190a61a14c3c41ed641 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c00e3fb48190a242264358413b05 |
completed | March 4, 2026, 5:15 a.m. |
Created at: March 1, 2026, 7:38 p.m.