Triple
T31079634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Against Ctesiphon |
E792063
|
entity |
| Predicate | legalChargeType |
P71082
|
FINISHED |
| Object | proposal contrary to existing laws |
—
|
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: proposal contrary to existing laws | Statement: [Against Ctesiphon, legalChargeType, proposal contrary to existing laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalChargeType Context triple: [Against Ctesiphon, legalChargeType, proposal contrary to existing laws]
-
A.
legalCharge
Indicates that an authority has formally accused an entity of committing a specific legal offense or violation.
-
B.
chargeType
chosen
Indicates the category or nature of a charge applied in a transaction or interaction between entities (e.g., fee type, billing classification, or legal charge type).
-
C.
fieldCharge
Indicates a relationship where an entity is assigned, responsible for, or associated with a particular field-related duty, task, or area of oversight.
-
D.
feeType
Indicates the specific category or classification of a fee associated with a transaction, service, or obligation.
-
E.
chargingInstrumentTypes
Indicates the types of instruments or tools used to perform a charging action in a given context.
- 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_69f224ccdbbc81909b0cdb4cc2d70c7a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe7b1c506c8190869c1a22031e0571 |
completed | May 9, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69fe796b2bdc8190a86980d44008f875 |
completed | May 9, 2026, 12:01 a.m. |
Created at: April 29, 2026, 9:02 p.m.