Triple
T16768254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio São Francisco |
E407523
|
entity |
| Predicate | rankInBrazil |
P110883
|
FINISHED |
| Object | one of the longest rivers in Brazil |
—
|
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: one of the longest rivers in Brazil | Statement: [Rio São Francisco, rankInBrazil, one of the longest rivers in Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInBrazil Context triple: [Rio São Francisco, rankInBrazil, one of the longest rivers in Brazil]
-
A.
urbanAreaRankInBrazil
Indicates the relative position or ranking of an urban area compared to other urban areas within Brazil.
-
B.
rankInCountry
chosen
Indicates the position or standing of an entity within a specific country according to some ranking or ordered criterion.
-
C.
nameInBrazil
Indicates that an entity is known or referred to by a particular name specifically in the context of Brazil.
-
D.
rankingInCountry
Indicates the position or level an entity holds within an ordered list specific to a particular country.
-
E.
roleInBrazil
Indicates that an entity holds or held a specific role, position, or function within the context of Brazil.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b0349bc88190938750f1e5af192a |
completed | April 18, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.