Triple
T37963054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Region of Porto Alegre |
E947056
|
entity |
| Predicate | hasMainLagoon |
P26295
|
FINISHED |
| Object | Lagoa dos Patos |
E651374
|
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: Lagoa dos Patos | Statement: [Metropolitan Region of Porto Alegre, hasMainLagoon, Lagoa dos Patos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainLagoon Context triple: [Metropolitan Region of Porto Alegre, hasMainLagoon, Lagoa dos Patos]
-
A.
hasLagoon
chosen
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
-
B.
isLagoon
Indicates that a body of water is a lagoon, i.e., a shallow coastal or inland water area separated from a larger body of water by a barrier such as a sandbank, reef, or barrier island.
-
C.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
D.
lagoonType
Indicates the specific kind or classification of a lagoon associated with an entity.
-
E.
hasCentralPond
Indicates that something contains a pond located at or near its central area.
- F. None of above.
Provenance (4 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4118088ad8819082471e0d1a0b7de2 |
completed | June 28, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.