Triple
T35520166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Convention of Klosterzeven |
E1026529
|
entity |
| Predicate | placeTypeOfLocation |
P16688
|
FINISHED |
| Object | former monastery town |
—
|
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: former monastery town | Statement: [Convention of Klosterzeven, placeTypeOfLocation, former monastery town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeTypeOfLocation Context triple: [Convention of Klosterzeven, placeTypeOfLocation, former monastery town]
-
A.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
B.
regionTypeOfPlace
Indicates that a place belongs to or is categorized under a specific type of geographic or administrative region.
-
C.
cityTypeLocation
Indicates that a location is classified as a specific type of city (e.g., capital, metropolitan, coastal).
-
D.
places
Indicates that one entity assigns, positions, or puts another entity into a specific location, role, or context.
-
E.
connectsTypeOfPlace
Indicates a relationship where one place is linked or associated with another based on its type or category of location.
- 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_69f76dfe78b081908e2b14cb88dd8c00 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd67191cf88190b53ecbf5be3564e9 |
completed | May 8, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_69fd654fdaac81908e67e75194710f06 |
completed | May 8, 2026, 4:23 a.m. |
Created at: May 3, 2026, 4:04 p.m.