Triple
T29708697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parakar |
E751714
|
entity |
| Predicate | roadDistanceToZvartnotsInternationalAirport |
P168168
|
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: [Parakar, roadDistanceToZvartnotsInternationalAirport, approximately 3–5 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToZvartnotsInternationalAirport Context triple: [Parakar, roadDistanceToZvartnotsInternationalAirport, approximately 3–5 km]
-
A.
distanceToZakopane_km
Indicates the distance, measured in kilometers, between a given place and Zakopane.
-
B.
distanceToZurich_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Zurich.
-
C.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
-
D.
distanceFromZermatt
Indicates the spatial distance between an entity and the location Zermatt.
-
E.
distanceToStockholmArlandaAirport
Indicates the measured distance between a given location or entity and Stockholm Arlanda Airport.
- F. None of above. chosen
Provenance (4 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 28, 2026, 7:29 p.m.