Triple
T10819145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mantua |
E255316
|
entity |
| Predicate | hasISO3166-2ProvinceCode |
P42695
|
FINISHED |
| Object | CU-01 |
—
|
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: CU-01 | Statement: [Mantua, hasISO3166-2ProvinceCode, CU-01]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISO3166-2ProvinceCode Context triple: [Mantua, hasISO3166-2ProvinceCode, CU-01]
-
A.
ISO3166-2RegionCode
chosen
Indicates the standardized ISO 3166-2 code that specifies the particular primary administrative subdivision (such as a state, province, or region) to which an entity belongs.
-
B.
associatedSubdivisionISO3166-1Alpha2
Indicates that a subdivision (such as a state or province) is associated with a specific country identified by its ISO 3166-1 alpha-2 code.
-
C.
hasISO3166-1NumericCode
Indicates that an entity is associated with a specific ISO 3166-1 numeric country code.
-
D.
associatedProvinceOrState
Indicates that one entity is linked or related to a specific province or state as its relevant administrative region.
-
E.
hasProvinceName
Indicates that an entity (such as a province or region) bears or is associated with a specific province name.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734492be88190874ea0ba4d0fa643 |
completed | April 9, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:18 p.m.