Triple
T28370203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regierungsbezirk Münster |
E718603
|
entity |
| Predicate | hasCityWithUniversity |
P49928
|
FINISHED |
| Object | Münster |
—
|
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: Münster | Statement: [Regierungsbezirk Münster, hasCityWithUniversity, Münster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityWithUniversity Context triple: [Regierungsbezirk Münster, hasCityWithUniversity, Münster]
-
A.
containsUniversityCity
chosen
Indicates that a given region or area includes within its boundaries a city that hosts a university.
-
B.
hasUniversityCityReputation
Indicates that a university holds a particular reputation or standing within a specific city.
-
C.
hasPublicUniversityCampus
Indicates that a public university maintains or operates a campus at the specified location.
-
D.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
E.
universityLocatedIn
Indicates that a university is situated within or associated with a specific geographic location or administrative region.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 28, 2026, 12:59 a.m.