Triple
T15016920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faraya–Mzaar ski area |
E377980
|
entity |
| Predicate | drivingTimeFromBeirut |
P116399
|
FINISHED |
| Object | about 1 hour |
—
|
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 1 hour | Statement: [Faraya–Mzaar ski area, drivingTimeFromBeirut, about 1 hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingTimeFromBeirut Context triple: [Faraya–Mzaar ski area, drivingTimeFromBeirut, about 1 hour]
-
A.
distanceFromBeirut
Indicates the measured spatial distance between a given entity’s location and the city of Beirut.
-
B.
distanceToLebanonBorder
Indicates the measured or estimated spatial distance between a given location and the border of Lebanon.
-
C.
distanceFromBeersheba
Indicates the spatial distance between a given location or entity and Beersheba.
-
D.
distanceToTunis
Indicates the spatial distance between a given entity’s location and the city of Tunis.
-
E.
distanceToAleppo
Indicates the spatial distance between a given entity and the location of Aleppo.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7633fcc8190b2231f43252bc46f |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:55 a.m.