Triple
T28592115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Çubuk district |
E723677
|
entity |
| Predicate | distanceToAnkaraCityCenter_km |
P106572
|
FINISHED |
| Object | approximately 40 |
—
|
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 40 | Statement: [Çubuk district, distanceToAnkaraCityCenter_km, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAnkaraCityCenter_km Context triple: [Çubuk district, distanceToAnkaraCityCenter_km, approximately 40]
-
A.
distanceToAnkara
chosen
Indicates the spatial distance between a given entity’s location and the city of Ankara.
-
B.
distanceFromKayseri
Indicates the spatial distance between a given entity and the location of Kayseri.
-
C.
distanceToGaziantep_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Gaziantep.
-
D.
distanceFromAlmaty_km
Indicates the distance, measured in kilometers, between a given place or object and the city of Almaty.
-
E.
distanceToIstanbulApproxKm
Indicates the approximate distance, measured in kilometers, between a given place and Istanbul.
- 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_69f01d7f92e481909847f5f3f3174a89 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a002962f6e081909906d6436bae6407 |
completed | May 10, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_6a00284c9c7c8190a77f18a41eee55df |
completed | May 10, 2026, 6:40 a.m. |
Created at: April 28, 2026, 4:20 a.m.