Triple
T24926764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paula Rosalee Corbin |
E618878
|
entity |
| Predicate | lawsuitSettlementAmount |
P89737
|
FINISHED |
| Object | $850,000 |
—
|
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: $850,000 | Statement: [Paula Rosalee Corbin, lawsuitSettlementAmount, $850,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawsuitSettlementAmount Context triple: [Paula Rosalee Corbin, lawsuitSettlementAmount, $850,000]
-
A.
legalActionSettlementAmount
chosen
Indicates the monetary amount agreed upon or ordered to resolve a legal action or dispute.
-
B.
lawsuitSettlementYear
Indicates the year in which a lawsuit between parties was formally settled or resolved.
-
C.
civilJudgmentAmount
Indicates the monetary value ordered or determined in a civil court judgment between parties.
-
D.
settlementWith
Indicates a relationship where one party reaches or maintains a settlement or agreement with another party, typically resolving a dispute or claim.
-
E.
settledAs
Indicates that one entity has been resolved, finalized, or agreed upon in the form or status of 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_69e2fab9edd88190b86004a78a28bc20 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 5:29 a.m.