Triple
T1013853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welsh Guards |
E21885
|
entity |
| Predicate | distinguishingMark |
P14118
|
FINISHED |
| Object | five buttons in groups of five on tunic front |
—
|
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: five buttons in groups of five on tunic front | Statement: [Welsh Guards, distinguishingMark, five buttons in groups of five on tunic front]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinguishingMark Context triple: [Welsh Guards, distinguishingMark, five buttons in groups of five on tunic front]
-
A.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
B.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
-
C.
symbolOnInsignia
Indicates that a particular symbol appears on or is featured as part of an insignia.
-
D.
distinguishingNotation
Indicates that one entity uses a specific notation or symbol to distinguish or differentiate another entity from similar ones.
-
E.
isDistinguishedBy
chosen
Indicates that one entity is characterized or set apart from others by a particular feature, quality, or attribute.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7be907c8190b5c6ea89257755a7 |
completed | March 1, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69a4b72207c08190a3dbb2aa7acbbc71 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.