Triple
T942215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sundbyberg Municipality |
E20330
|
entity |
| Predicate | isSmallAreaMunicipality |
P22015
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sundbyberg Municipality, isSmallAreaMunicipality, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSmallAreaMunicipality Context triple: [Sundbyberg Municipality, isSmallAreaMunicipality, true]
-
A.
isSmallCity
Indicates that a city has a relatively small population size or limited geographic/urban extent compared to typical cities.
-
B.
isSmallestByAreaIn
Indicates that an entity has the smallest area among all comparable entities within a specified set, group, or context.
-
C.
isSubProvincialCity
Indicates that a city holds a sub-provincial administrative status, ranking below a province but above ordinary prefecture-level cities in the governmental hierarchy.
-
D.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
-
E.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
- 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.