Triple
T25738741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slivnitsa Municipality |
E648154
|
entity |
| Predicate | capitalProximity |
P117282
|
FINISHED |
| Object | near Sofia |
—
|
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: near Sofia | Statement: [Slivnitsa Municipality, capitalProximity, near Sofia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capitalProximity Context triple: [Slivnitsa Municipality, capitalProximity, near Sofia]
-
A.
isNearCapitalCity
chosen
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
B.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
C.
regionCapitalNearby
Indicates that a capital city of a region is located close to the referenced place or entity.
-
D.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 22, 2026, 3:38 a.m.