Triple
T9309079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cutter |
E223962
|
entity |
| Predicate | opposingPartyRole |
P21000
|
FINISHED |
| Object | state corrections official |
—
|
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: state corrections official | Statement: [Cutter, opposingPartyRole, state corrections official]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposingPartyRole Context triple: [Cutter, opposingPartyRole, state corrections official]
-
A.
opposesPartyType
Indicates that one party or entity is in opposition to, or acts against the interests or positions of, a particular type or category of party.
-
B.
roleWhenInOpposition
chosen
Indicates the specific role or function an entity assumes when it is in a state of opposition to another entity or group.
-
C.
opponentInCase
Indicates that two parties are on opposing sides in the same legal case or proceeding.
-
D.
petitionerRole
Indicates the role or capacity in which a petitioner is acting within a legal or formal proceeding.
-
E.
isOppositionCounterpartOf
Indicates a relationship where one entity serves as the opposing or counterpart force, side, or position to another within a conflict, competition, or contrast.
- 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd1daba67c819081d53545d67ef127 |
completed | April 1, 2026, 1:29 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:37 p.m.