Triple
T16075642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horemheb |
E389972
|
entity |
| Predicate | aimOfReforms |
P39456
|
FINISHED |
| Object | curbing corruption among officials |
—
|
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: curbing corruption among officials | Statement: [Horemheb, aimOfReforms, curbing corruption among officials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimOfReforms Context triple: [Horemheb, aimOfReforms, curbing corruption among officials]
-
A.
goalOfReforms
chosen
Indicates that a reform or set of reforms is undertaken with the aim or intended objective of achieving a particular outcome.
-
B.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
C.
associatedReforms
Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
-
D.
causeOfReform
Indicates that one event, condition, or factor is the reason or driving force behind a particular reform or change in policy, structure, or practice.
-
E.
implementedReformsIn
Indicates that an entity (typically a person, organization, or government) carried out or put into effect specific reforms within a particular context, domain, or location.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1827ad7c88190b867da511cbfb7fa |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:57 a.m.