Triple
T10968467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Coloradas |
E259167
|
entity |
| Predicate | colorOfLagoonsCausedBy |
P96903
|
FINISHED |
| Object | microalgae |
—
|
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: microalgae | Statement: [Las Coloradas, colorOfLagoonsCausedBy, microalgae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorOfLagoonsCausedBy Context triple: [Las Coloradas, colorOfLagoonsCausedBy, microalgae]
-
A.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
B.
hasWaterColor
Indicates that an entity possesses or is characterized by a particular color of water.
-
C.
lagoonType
Indicates the specific kind or classification of a lagoon associated with an entity.
-
D.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
E.
mouthLake
Indicates the location where a river or stream flows into and forms part of a lake.
- F. None of above. chosen
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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7719800388190943a0bffa48a2731 |
completed | April 9, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.