Triple
T2566785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperator |
E57368
|
entity |
| Predicate | semanticShift |
P6522
|
FINISHED |
| Object | from general military commander to emperor |
—
|
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: from general military commander to emperor | Statement: [Imperator, semanticShift, from general military commander to emperor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: semanticShift Context triple: [Imperator, semanticShift, from general military commander to emperor]
-
A.
lexicalChange
chosen
Indicates a relationship where one linguistic form is replaced, modified, or evolves into another form over time or across language varieties.
-
B.
semanticRootMeaning
Indicates the fundamental or core meaning that underlies a word, phrase, or expression in a semantic structure.
-
C.
marksShiftToward
Indicates a change or transition from one state, condition, or position toward another, highlighting the direction or trend of that shift.
-
D.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
E.
narrativeShift
Indicates a change in the narrative perspective, time, focus, or structure within a story or discourse.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3602ed08190aad0f9c7ac577eb0 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.