Triple
T30713121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Párkány |
E781945
|
entity |
| Predicate | nearbyCapital |
P36605
|
FINISHED |
| Object | Budapest (relatively nearby along the Danube) |
—
|
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: Budapest (relatively nearby along the Danube) | Statement: [Párkány, nearbyCapital, Budapest (relatively nearby along the Danube)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCapital Context triple: [Párkány, nearbyCapital, Budapest (relatively nearby along the Danube)]
-
A.
nearbyTraditionalCapital
Indicates that one location is geographically close to a place that serves or served as a traditional capital.
-
B.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
regionCapitalNearby
Indicates that a capital city of a region is located close to the referenced place or entity.
-
D.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
E.
countyCapitalNearby
Indicates that a county’s capital city is located close to a specified place or 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 29, 2026, 8:35 p.m.