Triple
T7620395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Antwerp |
E172475
|
entity |
| Predicate | hasMunicipalitiesCount |
P30910
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Arrondissement of Antwerp, hasMunicipalitiesCount, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalitiesCount Context triple: [Arrondissement of Antwerp, hasMunicipalitiesCount, 30]
-
A.
hasNumberOfMunicipalities
chosen
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
B.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
C.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
-
D.
hasMunicipalFormation
Indicates that an administrative or territorial unit is organized into, or associated with, a specific municipal formation as its local self-governing structure.
-
E.
hasMunicipalDistrictNumber
Indicates that a municipality or local administrative unit is assigned a specific district number within its municipal structure.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.