Triple
T32279587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palea Kameni |
E824652
|
entity |
| Predicate | hasWaterColorNearShore |
P13022
|
FINISHED |
| Object | yellow-green from sulfur |
—
|
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: yellow-green from sulfur | Statement: [Palea Kameni, hasWaterColorNearShore, yellow-green from sulfur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterColorNearShore Context triple: [Palea Kameni, hasWaterColorNearShore, yellow-green from sulfur]
-
A.
hasWaterColor
chosen
Indicates that an entity possesses or is characterized by a particular color of water.
-
B.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
C.
hasNearbyCoast
Indicates that one location is situated close to a coastline or seashore.
-
D.
hasNearbyMarineFeature
Indicates that one entity is located close to a marine geographic feature associated with the other entity.
-
E.
hasEstuaryNear
Indicates that the estuary of a water body is located in close proximity to a specified place or feature.
- 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_69f3490f404081908450db66884f4334 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: May 1, 2026, 12:43 a.m.