Triple
T2480558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carolingian Empire |
E55803
|
entity |
| Predicate | administrativeOffice |
P39747
|
FINISHED |
| Object | count (comes) |
—
|
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: count (comes) | Statement: [Carolingian Empire, administrativeOffice, count (comes)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeOffice Context triple: [Carolingian Empire, administrativeOffice, count (comes)]
-
A.
mainOffice
Indicates that one location or office serves as the primary or central office for an organization or entity.
-
B.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
C.
basisOfOffice
Indicates the foundational principle, authority, or justification upon which an office or official position is established or exercised.
-
D.
otherOffice
Indicates that one office is an alternative or additional office associated with the same organization, person, or entity as another office.
-
E.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1e45380819094b3f32a278bd457 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.