Triple
T27653521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CH-NW |
E696926
|
entity |
| Predicate | standardizedNameOfSubdivision |
P50511
|
FINISHED |
| Object | Nidwalden |
—
|
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: Nidwalden | Statement: [CH-NW, standardizedNameOfSubdivision, Nidwalden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardizedNameOfSubdivision Context triple: [CH-NW, standardizedNameOfSubdivision, Nidwalden]
-
A.
subdivisionNameType
Indicates the type or category of a named geographic or administrative subdivision (e.g., province, state, district) associated with an entity.
-
B.
provincialSubdivisionName
Indicates the name assigned to a first-level administrative or provincial subdivision within a larger territorial or political entity.
-
C.
subdivisionNameLanguage
Indicates the language in which the name of a subdivision (such as a region, district, or administrative unit) is expressed.
-
D.
subdivisionISOName
chosen
Indicates the standardized ISO-recognized name assigned to a specific administrative subdivision within a country.
-
E.
scriptOfSubdivisionNames
Indicates that the specified writing system or script is used to represent the names of the subdivisions of a given entity.
- 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_69ef590abd3c8190834d0193bde12007 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 2:33 p.m.