Triple
T31695482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Companhia Docas do Estado de São Paulo |
E808905
|
entity |
| Predicate | operatedBusiestPortIn |
P200945
|
FINISHED |
| Object | Brazil |
—
|
NE NERFINISHED |
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: Brazil | Statement: [Companhia Docas do Estado de São Paulo, operatedBusiestPortIn, Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedBusiestPortIn Context triple: [Companhia Docas do Estado de São Paulo, operatedBusiestPortIn, Brazil]
-
A.
isBusiestLandPortBetween
Indicates that one location is the land port with the highest level of activity or traffic among a specified set of locations.
-
B.
operatedLargestPortIn
chosen
Indicates that an entity operated the largest port located within a specified geographic or political region.
-
C.
isBusiestTerminalOf
Indicates that one terminal is the busiest (i.e., handles the highest volume of activity) among all terminals associated with a given entity, such as an airport or transportation hub.
-
D.
isBusiestSeaportIn
Indicates that a seaport handles the highest volume of traffic or activity compared to all other seaports within a specified region or area.
-
E.
portTypeOperated
Indicates that one entity operates, manages, or runs the specified type of port associated with another entity.
- 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_69f348ddcbc48190950cabcc25ff29b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffbe9e47688190a2692566dc326646 |
completed | May 9, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69ffbb7b45388190b62cbde5c2d435cd |
completed | May 9, 2026, 10:55 p.m. |
Created at: April 30, 2026, 11:10 p.m.