Triple
T16387452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secular Franciscans |
E397959
|
entity |
| Predicate | hasRuleApprovedInYear |
P62976
|
FINISHED |
| Object | 1978 |
—
|
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: 1978 | Statement: [Secular Franciscans, hasRuleApprovedInYear, 1978]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuleApprovedInYear Context triple: [Secular Franciscans, hasRuleApprovedInYear, 1978]
-
A.
yearApproved
chosen
Indicates the specific year in which something (such as a proposal, product, or decision) was formally approved.
-
B.
hasOverrulingYear
Indicates the year in which a prior decision, rule, or action was formally overruled or invalidated.
-
C.
authorizationYear
Indicates the year in which an official approval, permission, or authorization for something was granted.
-
D.
assumedRuleYear
Indicates the year in which a particular rule, regulation, or policy is assumed to take effect or be applicable.
-
E.
hasApprovalType
Indicates that an entity is associated with a specific category or kind of approval it has received or requires.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263e1534819081a6bf5006c611c5 |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.