Triple
T402478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praia de São Rafael |
E9314
|
entity |
| Predicate | hasWaterColor |
P13022
|
FINISHED |
| Object | turquoise |
—
|
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: turquoise | Statement: [Praia de São Rafael, hasWaterColor, turquoise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterColor Context triple: [Praia de São Rafael, hasWaterColor, turquoise]
-
A.
appliesToWaterBody
Indicates that something (such as a rule, condition, property, or effect) is relevant or applicable specifically to a particular water body.
-
B.
hasHydrosphere
Indicates that an entity possesses or is characterized by a surrounding layer or system of water, such as oceans, seas, lakes, or other bodies of liquid water.
-
C.
includesWatersOff
Indicates that a geographic or administrative area’s scope explicitly extends to and covers the adjacent offshore waters.
-
D.
hasWaterBalance
Indicates that an entity maintains or exhibits a particular state or condition of water balance, such as hydration level or equilibrium between water intake and loss.
-
E.
hasStructureOnWatercourse
Indicates that a structure is physically located on, over, or directly associated with a specific watercourse.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eca0e2048190a7bf360257965e56 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96ee4ec8190a5c0e3f491d3963d |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.