Triple
T34353564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Belley-Ars |
E881650
|
entity |
| Predicate | coSeeCity |
P178903
|
FINISHED |
| Object | Ars-sur-Formans |
—
|
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: Ars-sur-Formans | Statement: [Diocese of Belley-Ars, coSeeCity, Ars-sur-Formans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coSeeCity Context triple: [Diocese of Belley-Ars, coSeeCity, Ars-sur-Formans]
-
A.
seeCityType
Indicates that an entity observes or recognizes the classification or type of a city (e.g., metropolitan, rural, coastal).
-
B.
cityView
Indicates that one entity offers a view of, or overlooks, a city.
-
C.
cityPanorama
Indicates a wide, comprehensive visual view or representation of a cityscape, typically encompassing many of its features in a single scene.
-
D.
isUrbanSee
Indicates a relationship where a location or area is recognized or classified as an urban settlement or city-like environment.
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
- 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_69f349bd06008190904c2f86c42749e3 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71782422c81908196d5e4a610cb1a |
completed | May 3, 2026, 9:38 a.m. |
Created at: May 1, 2026, 1:58 a.m.