Triple
T382839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bourget Field |
E8716
|
entity |
| Predicate | distanceFromParisCenter |
P10703
|
FINISHED |
| Object | about 11 km northeast |
—
|
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 11 km northeast | Statement: [Le Bourget Field, distanceFromParisCenter, about 11 km northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromParisCenter Context triple: [Le Bourget Field, distanceFromParisCenter, about 11 km northeast]
-
A.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
B.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
C.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceFromNorthPole
Indicates the measured spatial distance between a given entity’s location and the geographic North Pole.
-
E.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec40ff8c81909306eb2dfe1512af |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.