Triple
T1093966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region of Waterloo International Airport |
E24228
|
entity |
| Predicate | distanceFromWaterloo |
P23804
|
FINISHED |
| Object | approximately 14 km east |
—
|
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 14 km east | Statement: [Region of Waterloo International Airport, distanceFromWaterloo, approximately 14 km east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromWaterloo Context triple: [Region of Waterloo International Airport, distanceFromWaterloo, approximately 14 km east]
-
A.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
D.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
E.
distanceFromLeeds
Indicates the spatial distance between a given entity and the location of Leeds.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.