Triple
T21757489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clonmacnoise |
E537077
|
entity |
| Predicate | numberOfHighCrosses |
P52834
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Clonmacnoise, numberOfHighCrosses, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHighCrosses Context triple: [Clonmacnoise, numberOfHighCrosses, 3]
-
A.
hasNumberOfCrosses
chosen
Indicates the quantity of crosses associated with or present on a given entity.
-
B.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
C.
crossesUnder
Indicates that one entity passes beneath another entity’s path or structure, moving from one side to the other without intersecting it at the same elevation.
-
D.
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.
-
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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8f64d881909cf10fd420153b09 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969e46088190b13d6e9025775ea3 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.