Triple
T3307712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garter motto "Honi soit qui mal y pense" |
E69489
|
entity |
| Predicate | literalComponents |
P16024
|
FINISHED |
| Object | honi |
—
|
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: honi | Statement: [Garter motto "Honi soit qui mal y pense", literalComponents, honi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literalComponents Context triple: [Garter motto "Honi soit qui mal y pense", literalComponents, honi]
-
A.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
B.
symbolText
Indicates that a symbol is associated with or represented by a specific piece of text.
-
C.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
D.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
E.
logicalForm
Indicates a relationship where an expression is associated with its structured, formal logical representation.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0cc15088190b51c311c6590df04 |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.