Triple
T18020143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shipwreck Beach |
E431093
|
entity |
| Predicate | waterColorDescription |
P10891
|
FINISHED |
| Object | intense blue |
—
|
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: intense blue | Statement: [Shipwreck Beach, waterColorDescription, intense blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterColorDescription Context triple: [Shipwreck Beach, waterColorDescription, intense blue]
-
A.
waterColor
chosen
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.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
D.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
E.
waveColor
Indicates the color associated with a particular wave (e.g., light or electromagnetic wave) in the described context.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c1c5f88190a059ce4f86f7ed36 |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.