Triple
T8451548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .yt |
E199809
|
entity |
| Predicate | RFCCategory |
P87
|
FINISHED |
| Object | country-code top-level domain |
—
|
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: country-code top-level domain | Statement: [.yt, RFCCategory, country-code top-level domain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RFCCategory Context triple: [.yt, RFCCategory, country-code top-level domain]
-
A.
hasChemicalClass
Indicates that an entity belongs to, or is categorized under, a particular chemical class based on its structural or compositional characteristics.
-
B.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
-
C.
textCategory
Indicates that a piece of text belongs to or is classified under a particular category or type.
-
D.
categoryLabel_H
Indicates that an entity is assigned a human-readable category label or classification.
-
E.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44815488190a912d63512e19af0 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.