Triple
T8958894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elwha River |
E213547
|
entity |
| Predicate | restorationCost |
P51456
|
FINISHED |
| Object | over 300 million US dollars |
—
|
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: over 300 million US dollars | Statement: [Elwha River, restorationCost, over 300 million US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restorationCost Context triple: [Elwha River, restorationCost, over 300 million US dollars]
-
A.
estimatedCost
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
B.
hasRenovationCost
Indicates that an entity is associated with a specific monetary cost required for its renovation.
-
C.
restorationMeasure
Indicates that an action or intervention is undertaken to repair, rehabilitate, or return something to a previous or improved state.
-
D.
restorationReason
Indicates the reason or justification for which something that was previously removed, disabled, or altered has been restored to its former state.
-
E.
reconstructionCost
chosen
Indicates the monetary or resource expenditure required to rebuild or restore something to its prior or intended state.
- 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_69ca8399ad2081909f8fa41d4314c215 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc672b12b48190a9d964f79b96d237 |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7 p.m.