Triple
T3541830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apure River |
E74903
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Llanos |
E58230
|
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: Llanos | Statement: [Apure River, locatedIn, Llanos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Llanos Context triple: [Apure River, locatedIn, Llanos]
-
A.
Orinoco Llanos floodplains
chosen
The Orinoco Llanos floodplains are vast seasonally inundated grasslands in the Orinoco River basin of Venezuela and Colombia, known for their rich biodiversity and extensive wetlands.
-
B.
Isabela plains
Isabela plains is a broad, fertile lowland area in the Philippine province of Isabela, known as one of the country’s major agricultural regions.
-
C.
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.
-
D.
Pampa
Pampa is a small city in the Texas Panhandle known historically for its role in the oil and gas industry and as a regional service and trade center.
-
E.
Orinoco Belt
The Orinoco Belt is a vast oil-rich region in eastern Venezuela known for containing one of the world’s largest extra-heavy crude oil reserves.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbf73c5e881909a8352512928377b |
completed | March 8, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bb8b7fac81908c18d3f868aeba44 |
completed | March 13, 2026, 7:23 a.m. |
Created at: March 8, 2026, 3:20 p.m.