Triple
T22590478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rices Landing, Pennsylvania |
E564933
|
entity |
| Predicate | primaryRiverUseHistorical |
P133771
|
FINISHED |
| Object | coal shipping |
—
|
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: coal shipping | Statement: [Rices Landing, Pennsylvania, primaryRiverUseHistorical, coal shipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRiverUseHistorical Context triple: [Rices Landing, Pennsylvania, primaryRiverUseHistorical, coal shipping]
-
A.
hasRiverUse
Indicates that one entity makes use of a river associated with another entity, such as for transport, irrigation, recreation, or other purposes.
-
B.
watercourseHistory
chosen
Indicates that there exists a historical or past relationship, state, or condition associated with a particular watercourse.
-
C.
reservoirUse
Indicates the way a reservoir is utilized or the purpose for which its stored water is used.
-
D.
historicallyAssociatedRiver
Indicates a relationship where an entity has a notable historical connection or association with a particular river, such as through events, development, or cultural significance.
-
E.
basinUse
Indicates that a basin is used for a particular purpose, activity, or function.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615f63788190acf776b313f0794a |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:48 p.m.