Triple
T21808618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klonk |
E538412
|
entity |
| Predicate | distanceFromPragueApprox |
P59333
|
FINISHED |
| Object | about 30 km southwest |
—
|
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: about 30 km southwest | Statement: [Klonk, distanceFromPragueApprox, about 30 km southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPragueApprox Context triple: [Klonk, distanceFromPragueApprox, about 30 km southwest]
-
A.
distanceFromPragueKmApprox
chosen
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
-
B.
distanceFromBrno
Indicates the spatial distance between a given entity and the city of Brno.
-
C.
distanceFromPlzeň_km
Indicates the distance, measured in kilometers, between an entity and the city of Plzeň.
-
D.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
E.
distanceToJihlava
Indicates the spatial distance between a given entity’s location and the city of Jihlava.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f078047ca88190a0efa4bc7f2faf80 |
completed | April 28, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:53 p.m.