Triple
T21986878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museumstrasse |
E542984
|
entity |
| Predicate | hasAssociatedPlaceType |
P128043
|
FINISHED |
| Object | station area |
—
|
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: station area | Statement: [Museumstrasse, hasAssociatedPlaceType, station area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedPlaceType Context triple: [Museumstrasse, hasAssociatedPlaceType, station area]
-
A.
hasAssociatedType
chosen
Indicates that one entity is linked to another entity that specifies its type, category, or classification.
-
B.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
-
C.
hasTerritorialAssociation
Indicates a relationship where an entity is linked or connected to a specific territory, area, or geographic region.
-
D.
hasToponymicAssociation
Indicates a relationship where one entity is associated with, derived from, or named after a particular place or geographic name (toponym).
-
E.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12709cb288190a2620e337fea364c |
completed | April 28, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:04 p.m.