Triple
T30400413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the Recollects |
E773331
|
entity |
| Predicate | hasCanonicalStructure |
P195680
|
FINISHED |
| Object | provinces |
—
|
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: provinces | Statement: [Order of the Recollects, hasCanonicalStructure, provinces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalStructure Context triple: [Order of the Recollects, hasCanonicalStructure, provinces]
-
A.
hasCanonicalRepresentation
Indicates that one entity is the standard or authoritative form in which another entity is represented.
-
B.
isCanonical
Indicates that something represents the standard, authoritative, or officially accepted form within a given context or system.
-
C.
hasCanonicalReference
Indicates that one entity serves as the authoritative or standard reference source for another entity.
-
D.
hasRealStructure
Indicates that an abstract object or system is endowed with a concrete, well-defined mathematical or physical structure that makes it realizable or interpretable in a real-world or formal model.
-
E.
hasCanonicalDecomposition
Indicates that an entity can be expressed as a standard or normalized combination of more basic components or parts.
- 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_69f2248facd48190b183c3f3ca6daef7 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: April 29, 2026, 8:03 p.m.