Triple
T13441847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KRK |
E320380
|
entity |
| Predicate | airportLocationRelativeToCity |
P82169
|
FINISHED |
| Object | west of Kraków city 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: west of Kraków city centre | Statement: [KRK, airportLocationRelativeToCity, west of Kraków city centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportLocationRelativeToCity Context triple: [KRK, airportLocationRelativeToCity, west of Kraków city centre]
-
A.
airportLocatedNear
Indicates that an airport is situated close to a specified place or geographic feature.
-
B.
airportLocatedIn
Indicates that an airport is geographically situated within a specific administrative or territorial area.
-
C.
airportLocationRelation
chosen
Indicates a spatial or administrative relationship specifying where an airport is located relative to a geographic area or jurisdiction.
-
D.
airportLocatedWithin
Indicates that an airport is geographically situated inside the boundaries of a specified area or region.
-
E.
associatedAirportLocalName
Indicates the local or native-language name of the airport that is associated with the given entity.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee704ac8190b4c7f4e0d3a88494 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.