Triple
T14132467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Launceston Airport |
E350201
|
entity |
| Predicate | distanceFromCity_km |
P1299
|
FINISHED |
| Object | about 15 |
—
|
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 15 | Statement: [Launceston Airport, distanceFromCity_km, about 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCity_km Context triple: [Launceston Airport, distanceFromCity_km, about 15]
-
A.
distanceFromMajorCity
Indicates the measured distance between a given location and a specified major city.
-
B.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
C.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
E.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610cece88190b4a86500677e5938 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 11:24 p.m.