Triple
T14243103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagoa Negra |
E353060
|
entity |
| Predicate | waterSurfaceAppearance |
P60967
|
FINISHED |
| Object | dark-hued |
—
|
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: dark-hued | Statement: [Lagoa Negra, waterSurfaceAppearance, dark-hued]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterSurfaceAppearance Context triple: [Lagoa Negra, waterSurfaceAppearance, dark-hued]
-
A.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
B.
waterAppearance
chosen
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
C.
hasWaterColor
Indicates that an entity possesses or is characterized by a particular color of water.
-
D.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
E.
surfaceWater
Indicates that one entity consists of or contains surface-level water 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6244ad188190b9d9db7914240410 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.