Triple
T38353965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Verden |
E1046272
|
entity |
| Predicate | underMetropolitan |
P195715
|
FINISHED |
| Object | Archdiocese of Mainz |
—
|
NE NERFINISHED |
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: Archdiocese of Mainz | Statement: [Diocese of Verden, underMetropolitan, Archdiocese of Mainz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underMetropolitan Context triple: [Diocese of Verden, underMetropolitan, Archdiocese of Mainz]
-
A.
metropolitan
Indicates that a location is part of, belongs to, or lies within a specified metropolitan (urban) area.
-
B.
cityBelow
Indicates that one city is geographically located at a lower elevation or vertical position relative to another city.
-
C.
withinUrbanArea
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
-
D.
isSmallMetroArea
Indicates that a metropolitan area has a relatively small population size or geographic extent compared to typical metro areas.
-
E.
metropolitanThreshold
Indicates that a place has reached or exceeded the population or density level required to be classified as a metropolitan area.
- 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_69f76e3a94fc81908edc175e8d259e80 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: May 3, 2026, 4:31 p.m.