Triple
T29350681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venice of Provence |
E744300
|
entity |
| Predicate | appliedToRegionType |
P137247
|
FINISHED |
| Object | Provençal 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: Provençal town | Statement: [Venice of Provence, appliedToRegionType, Provençal town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToRegionType Context triple: [Venice of Provence, appliedToRegionType, Provençal town]
-
A.
appliesToRegionType
chosen
Indicates that something is relevant or applicable specifically to a particular type or category of region.
-
B.
containsRegionType
Indicates that one region includes or encompasses another region of a specified type within its spatial or logical boundaries.
-
C.
appliedToGroupType
Indicates that something (such as a rule, setting, or action) is applied specifically to a particular type or category of group rather than to individual members.
-
D.
isPartOfRegionType
Indicates that one region belongs to, or is classified under, a broader region type or category.
-
E.
appliesToSegmentType
Indicates that a rule, condition, or operation is specifically associated with and relevant to a particular type of segment.
- 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_69f0a79a2d748190bc30abd469298b37 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 28, 2026, 2:06 p.m.