Triple
T17681179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Manaus |
E440772
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Amazonas state |
E438768
|
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: Amazonas state | Statement: [Port of Manaus, serves, Amazonas state]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazonas state Context triple: [Port of Manaus, serves, Amazonas state]
-
A.
Amazonas state
chosen
Amazonas state is Brazil’s largest and mostly rainforest-covered state in the northwest of the country, known for encompassing much of the Amazon River basin and the city of Manaus.
-
B.
Amazonas state
Amazonas state is a vast, sparsely populated region in southern Venezuela known for its Amazon rainforest, indigenous communities, and rich biodiversity.
-
C.
Pará
Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
-
D.
Roraima state
Roraima state is Brazil’s northernmost and least populated state, located in the Amazon region and known for its vast savannas, indigenous communities, and the iconic Mount Roraima.
-
E.
Aragua state
Aragua state is a central Venezuelan state known for its capital city Maracay, industrial activity, and diverse landscapes that include coastal areas and national parks.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470445b3881908bb0930b986089f7 |
completed | April 19, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a030c4c80b48190b45e751038ca73fd |
completed | May 12, 2026, 11:17 a.m. |
Created at: April 10, 2026, 10:01 a.m.