Triple
T28974579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhûn |
E734372
|
entity |
| Predicate | hasCanonicalDetailLevel |
P192982
|
FINISHED |
| Object | sparse |
—
|
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: sparse | Statement: [Rhûn, hasCanonicalDetailLevel, sparse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalDetailLevel Context triple: [Rhûn, hasCanonicalDetailLevel, sparse]
-
A.
hasTopographicDetailLevel
Indicates the degree of granularity or resolution at which the topographic characteristics of something are represented or described.
-
B.
hasCanonicalAspect
Indicates that an entity is associated with its standard or officially recognized aspect, form, or representation.
-
C.
hasStandardizationLevel
Indicates the degree or extent to which something conforms to an established standard or set of standardized criteria.
-
D.
hasCanonicalRelevance
Indicates that something is considered standard, authoritative, or centrally important within an established canon or reference framework.
-
E.
hasNoFurtherSubdivisionLevel
Indicates that the referenced entity is at the lowest level of subdivision and cannot be further subdivided into smaller units within the given hierarchy.
- 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
| PDg | Predicate description generation | batch_69fd35d029588190a525aa8a506e7708 |
completed | May 8, 2026, 1:01 a.m. |
Created at: April 28, 2026, 9:07 a.m.