Triple
T26653912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Vodno |
E666441
|
entity |
| Predicate | distanceToSkopjeCenter |
P128132
|
FINISHED |
| Object | approximately 3–5 km |
—
|
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: approximately 3–5 km | Statement: [Mount Vodno, distanceToSkopjeCenter, approximately 3–5 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSkopjeCenter Context triple: [Mount Vodno, distanceToSkopjeCenter, approximately 3–5 km]
-
A.
distanceToSkopje_km
chosen
Indicates the physical distance, measured in kilometers, between a given place and the city of Skopje.
-
B.
directionFromSkopje
Indicates the cardinal or relative compass direction in which one entity is located when measured from Skopje.
-
C.
distanceToBelgrade
Indicates the spatial distance between a given entity and the city of Belgrade.
-
D.
distanceToTirana_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Tirana.
-
E.
distanceFromPristina
Indicates the spatial distance between an entity’s location and the city of Pristina.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: April 27, 2026, 2:34 a.m.