Triple
T8664907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wateringen |
E205642
|
entity |
| Predicate | hasMunicipalFacility |
P80014
|
FINISHED |
| Object | local shopping centre |
—
|
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: local shopping centre | Statement: [Wateringen, hasMunicipalFacility, local shopping centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalFacility Context triple: [Wateringen, hasMunicipalFacility, local shopping centre]
-
A.
hasMunicipalService
Indicates that a municipality provides or is responsible for a specific public service to a given area, facility, or population.
-
B.
hasCivicAmenity
chosen
Indicates that an entity possesses, provides, or is associated with a public facility or service intended for community use.
-
C.
hasMunicipalServiceProvider
Indicates that a municipality is served by a specific organization or entity that provides municipal services (such as utilities, waste management, or public transport).
-
D.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
E.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a0ae108190b33dadcc3cb18949 |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:30 p.m.