Triple
T27095429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capannoli |
E686281
|
entity |
| Predicate | provinceSubdivisionType |
P79356
|
FINISHED |
| Object | province |
—
|
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: province | Statement: [Capannoli, provinceSubdivisionType, province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: provinceSubdivisionType Context triple: [Capannoli, provinceSubdivisionType, province]
-
A.
countrySubdivisionType
Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
-
B.
politicalSubdivisionType
chosen
Indicates the specific category or level of governmental or administrative division that characterizes a political subdivision.
-
C.
countrySubdivisionTypeRepresented
Indicates that a given entity represents or corresponds to a specific type of country subdivision (such as a state, province, or region).
-
D.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
E.
censusSubdivisionType
Indicates the specific administrative or geographic category assigned to a census subdivision (e.g., city, town, rural area) within a census system.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 27, 2026, 8:44 a.m.