Triple
T5529162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constitution of Ireland |
E145002
|
entity |
| Predicate | articleCountApprox |
P64750
|
FINISHED |
| Object | 50+ |
—
|
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: 50+ | Statement: [Constitution of Ireland, articleCountApprox, 50+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: articleCountApprox Context triple: [Constitution of Ireland, articleCountApprox, 50+]
-
A.
articleCount
Indicates the number of articles associated with a given entity or context.
-
B.
articleNumber
Indicates that one entity is identified or referenced by a specific article number assigned to it.
-
C.
articleRange
Indicates that one entity specifies the start and end points of a contiguous range of articles that are grouped or referenced together.
-
D.
containsArticle
Indicates that one entity includes or holds an article (such as a written piece, item, or document) as part of its contents.
-
E.
numberOfManuscriptsApprox
Indicates an approximate count of manuscripts associated with an entity.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f996e088190844cba2c4458bd76 |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:34 p.m.