Triple
T35960387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krzeszów |
E1039977
|
entity |
| Predicate | nearestLargerAdministrativeCenter |
P42873
|
FINISHED |
| Object | Sucha Beskidzka |
—
|
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: Sucha Beskidzka | Statement: [Krzeszów, nearestLargerAdministrativeCenter, Sucha Beskidzka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestLargerAdministrativeCenter Context triple: [Krzeszów, nearestLargerAdministrativeCenter, Sucha Beskidzka]
-
A.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
B.
hasNearestLargerSettlement
chosen
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
C.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
D.
largestNearbyCity
Indicates that one city is the largest (by population, area, or another defined metric) among the cities located within a specified nearby region of another place or city.
-
E.
nearestInlandCity
Indicates that one city is the closest inland (non-coastal) city to another specified location.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.