Triple
T942220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sundbyberg Municipality |
E20330
|
entity |
| Predicate | hasSubdivisionCode |
P22016
|
FINISHED |
| Object | SE-0180 |
—
|
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: SE-0180 | Statement: [Sundbyberg Municipality, hasSubdivisionCode, SE-0180]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionCode Context triple: [Sundbyberg Municipality, hasSubdivisionCode, SE-0180]
-
A.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
B.
hasSubdivisionCodeContext
Indicates that a subdivision code is interpreted within a specific coding or contextual framework that defines its meaning.
-
C.
hasSubregionStatus
Indicates that one region holds an official or defined status as a subregion within a larger geographic or administrative area.
-
D.
representsSubdivisionOf
Indicates that one administrative or territorial unit is a smaller, constituent part of a larger administrative or territorial unit.
-
E.
hasStandardSubdivisionRange
Indicates that there is a defined range of standard subdivisions applicable to a given entity or classification.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a1a4888190997adf56eb761431 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29dc8dc8190b9d33f70f8563d61 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b344f6f48190ba03ce593c94176b |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.