Triple
T13325727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman aqueduct |
E317436
|
entity |
| Predicate | oftenCrosses |
P27425
|
FINISHED |
| Object | valleys |
—
|
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: valleys | Statement: [Roman aqueduct, oftenCrosses, valleys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenCrosses Context triple: [Roman aqueduct, oftenCrosses, valleys]
-
A.
oftenCrossedOn
Indicates that one entity is frequently traversed or passed over by another entity.
-
B.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
C.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
D.
crossesIn
chosen
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
E.
crossesTo
Indicates that one entity moves or extends from one side or area to another, passing over or through some boundary or intervening space.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:30 p.m.