Triple
T9014885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Guinea |
E215568
|
entity |
| Predicate | usedDrivingSide |
P250
|
FINISHED |
| Object | right |
—
|
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: right | Statement: [French Guinea, usedDrivingSide, right]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedDrivingSide Context triple: [French Guinea, usedDrivingSide, right]
-
A.
drivingSide
chosen
Indicates which side of the road (left or right) vehicles are required to drive on in a given jurisdiction.
-
B.
drivingSideChangeYear
Indicates the year in which a place officially changed the side of the road on which vehicles are required to drive.
-
C.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
D.
drivingExperience
Indicates the extent or history of a person's involvement in driving vehicles, typically measured by duration, frequency, or level of skill.
-
E.
bodySideOrientation
Indicates the spatial relationship of an entity with respect to the left, right, or bilateral side of a body.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69fae0b88190a0aa989bc37ab2c7 |
completed | April 1, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:06 p.m.