Triple
T5840517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viking textiles |
E129579
|
entity |
| Predicate | provideInsightInto |
P17720
|
FINISHED |
| Object | Viking craftsmanship |
—
|
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: Viking craftsmanship | Statement: [Viking textiles, provideInsightInto, Viking craftsmanship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: provideInsightInto Context triple: [Viking textiles, provideInsightInto, Viking craftsmanship]
-
A.
providesInformationIn
chosen
Indicates that one entity supplies or conveys information within or through another entity or context.
-
B.
providesIntelligenceTo
Indicates that one entity supplies information, analysis, or insight that enhances the knowledge or decision-making capability of another entity.
-
C.
providesGuidanceTo
Indicates that one entity offers direction, advice, or instruction to another entity.
-
D.
helpsAnalyze
Indicates that one entity assists another in examining, interpreting, or understanding something in a more detailed or effective way.
-
E.
providesExposureTo
Indicates that one entity gives another entity the opportunity to be seen, noticed, or become known by a particular audience, environment, or set of influences.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.