Triple
T13534303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clan Sutherland |
E323219
|
entity |
| Predicate | tartanType |
P10431
|
FINISHED |
| Object | Ancient Sutherland tartan |
—
|
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: Ancient Sutherland tartan | Statement: [Clan Sutherland, tartanType, Ancient Sutherland tartan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tartanType Context triple: [Clan Sutherland, tartanType, Ancient Sutherland tartan]
-
A.
tartan
chosen
Indicates that something has a tartan pattern or is characterized by a tartan design.
-
B.
textileType
Indicates the specific kind or category of textile material associated with an entity.
-
C.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
-
D.
typeOfTie
Indicates the specific kind or category of relationship or connection that exists between two entities.
-
E.
Typer
Indicates that one entity serves as the type or classification for 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbcad2881909fb7490311807f75 |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:44 p.m.