Triple
T13588670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | prince-abbeys |
E324634
|
entity |
| Predicate | wereDistinctFrom |
P1612
|
FINISHED |
| Object | secular principalities |
—
|
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: secular principalities | Statement: [prince-abbeys, wereDistinctFrom, secular principalities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wereDistinctFrom Context triple: [prince-abbeys, wereDistinctFrom, secular principalities]
-
A.
historicallyDistinctFrom
Indicates that two entities are recognized as separate and not the same in historical context, despite any similarities or connections they may have.
-
B.
isDistinctFrom
chosen
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
C.
mechanicallyDistinctFrom
Indicates that two entities differ in their mechanical properties, structure, or behavior such that they are not mechanically equivalent or interchangeable.
-
D.
differentiatedFrom
Indicates that one entity is distinguished or set apart from another by identifying differences between them.
-
E.
hasDistinctCultureFrom
Indicates that the culture of one entity is different and distinguishable from the culture of another entity.
- 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.