Triple
T34719176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revolutionary Court of Iraq |
E1000862
|
entity |
| Predicate | sentencingPower |
P181544
|
FINISHED |
| Object | capital punishment |
—
|
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: capital punishment | Statement: [Revolutionary Court of Iraq, sentencingPower, capital punishment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentencingPower Context triple: [Revolutionary Court of Iraq, sentencingPower, capital punishment]
-
A.
sentencedTo
Indicates that an authority has officially assigned a specific punishment or penalty to an entity, typically as the outcome of a legal or disciplinary process.
-
B.
sentencingYear
Indicates the calendar year in which a person or entity received a formal legal sentence or judgment.
-
C.
maximumImprisonmentPower
Indicates the highest duration or extent of imprisonment that an authority is legally empowered to impose.
-
D.
providesSentencingScheme
Indicates that one entity establishes or supplies the framework or set of rules used to determine legal sentences for offenses.
-
E.
clemencyPower
Indicates the authority to grant mercy or reduce or cancel penalties imposed on others.
- F. None of above. chosen
Provenance (4 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_69f76dad3f108190a280fd0a2f4ee89a |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77ff804f08190b431a31e6179ace4 |
completed | May 3, 2026, 5:03 p.m. |
Created at: May 3, 2026, 3:59 p.m.