Triple
T13588660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | prince-abbeys |
E324634
|
entity |
| Predicate | existedInRegion |
P8054
|
FINISHED |
| Object | German lands |
—
|
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: German lands | Statement: [prince-abbeys, existedInRegion, German lands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: existedInRegion Context triple: [prince-abbeys, existedInRegion, German lands]
-
A.
enforcedInRegion
Indicates that a rule, policy, or condition is actively applied and upheld within a specified geographic or administrative region.
-
B.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
C.
authorizedInRegion
Indicates that an entity has official permission or legal authority to operate, act, or be valid within a specified geographic or administrative region.
-
D.
observedInRegion
chosen
Indicates that something has been detected, recorded, or seen occurring within a specified geographic or spatial region.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.