Triple
T22056749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fisher Landing, Tennessee |
E545038
|
entity |
| Predicate | hasWaterRelatedCharacteristic |
P64067
|
FINISHED |
| Object | river access |
—
|
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: river access | Statement: [Fisher Landing, Tennessee, hasWaterRelatedCharacteristic, river access]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterRelatedCharacteristic Context triple: [Fisher Landing, Tennessee, hasWaterRelatedCharacteristic, river access]
-
A.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
B.
hasWaterBodyCharacteristic
Indicates that a water body possesses a specified physical, chemical, or ecological characteristic.
-
C.
hasWaterFeatures
chosen
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
-
D.
hasWaterColor
Indicates that an entity possesses or is characterized by a particular color of water.
-
E.
hasRiverineCharacteristic
Indicates that something possesses qualities, features, or conditions associated with rivers or river environments.
- 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128588e0081909056ac8251afe935 |
completed | April 28, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:27 p.m.