Triple
T9351052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbey of Hersfeld |
E225017
|
entity |
| Predicate | typeOfMonastery |
P37070
|
FINISHED |
| Object | imperial Benedictine abbey |
—
|
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: imperial Benedictine abbey | Statement: [Abbey of Hersfeld, typeOfMonastery, imperial Benedictine abbey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMonastery Context triple: [Abbey of Hersfeld, typeOfMonastery, imperial Benedictine abbey]
-
A.
monasteryType
chosen
Indicates the specific kind or classification of a monastery in relation to its broader religious or organizational category.
-
B.
monastery
Indicates that an entity is or functions as a monastery, typically a religious community or building where monastics live and practice.
-
C.
containsMonastery
Indicates that one entity includes or encompasses a monastery within its boundaries or composition.
-
D.
monasteryAffiliation
Indicates a relationship where an entity is formally associated with, belongs to, or is under the authority of a particular monastery.
-
E.
hasNearbyMonastery
Indicates that one entity is located close to or in the vicinity of a monastery.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f9248c08190a7bb40feec2eb217 |
completed | April 1, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:41 p.m.