Triple
T5806065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khan Krum |
E128745
|
entity |
| Predicate | legalReforms |
P61708
|
FINISHED |
| Object | codification of customary law (attributed) |
—
|
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: codification of customary law (attributed) | Statement: [Khan Krum, legalReforms, codification of customary law (attributed)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalReforms Context triple: [Khan Krum, legalReforms, codification of customary law (attributed)]
-
A.
legalReformer
Indicates that an entity works to change, improve, or modernize laws or legal systems.
-
B.
associatedWithLegalReforms
chosen
Indicates a relationship where an entity is connected to, involved in, or influenced by specific legal reforms or changes in law.
-
C.
legalAmendment
Indicates a formal change or modification made to an existing law, regulation, or legal document.
-
D.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
E.
constitutionalReformSubject
Indicates that an entity is the subject or focus of a constitutional reform process, proposal, or change.
- 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_69c00846a0d881909e46841f8e156b64 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b15d8108190b434da42631c4e0c |
completed | March 22, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.