Triple
T10071604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Francisco River |
E213640
|
entity |
| Predicate | rankByLengthInBrazil |
P18229
|
FINISHED |
| Object | oneOfLongestRiversInBrazil |
—
|
LITERAL 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: oneOfLongestRiversInBrazil | Statement: [São Francisco River, rankByLengthInBrazil, oneOfLongestRiversInBrazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByLengthInBrazil Context triple: [São Francisco River, rankByLengthInBrazil, oneOfLongestRiversInBrazil]
-
A.
urbanAreaRankInBrazil
Indicates the relative position or ranking of an urban area compared to other urban areas within Brazil.
-
B.
rankByLength
chosen
Indicates ordering a set of items based on their length, typically from shortest to longest or vice versa.
-
C.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
D.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
-
E.
countryNamePortuguese
Indicates the Portuguese-language name assigned to a given country.
- F. None of above.
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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd01279388190b94c8def00425c78 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.