Triple
T4676450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver Falls |
E103692
|
entity |
| Predicate | waterColorCause |
P23298
|
FINISHED |
| Object | high calcium carbonate content |
—
|
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: high calcium carbonate content | Statement: [Beaver Falls, waterColorCause, high calcium carbonate content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterColorCause Context triple: [Beaver Falls, waterColorCause, high calcium carbonate content]
-
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.
colorationCause
chosen
Indicates that one entity is the cause or source of the coloration observed in another entity.
-
D.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
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_69bd43dda32c8190938b37744ca270fc |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.