Triple
T37845328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | court-martial of Admiral John Byng |
E943583
|
entity |
| Predicate | hasQuotations |
P78667
|
FINISHED |
| Object | "pour encourager les autres" |
—
|
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: "pour encourager les autres" | Statement: [court-martial of Admiral John Byng, hasQuotations, "pour encourager les autres"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuotations Context triple: [court-martial of Admiral John Byng, hasQuotations, "pour encourager les autres"]
-
A.
containsQuotationMarks
Indicates that the referenced text includes one or more quotation mark characters within it.
-
B.
hasQuotationSystem
Indicates that an entity uses or is associated with a particular system or convention for representing quotations.
-
C.
hasQuotationStatus
Indicates that an entity has a particular quotation-related state or condition (such as being quoted, unquoted, or having a specific quotation status).
-
D.
quotedOn
Indicates that one entity is cited, referenced, or mentioned within another source, document, or context.
-
E.
quotationText
chosen
Indicates that the associated text is the exact content of a quotation made or referenced in the relationship.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc995dc2481908b3bd4217f8101e7 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:19 p.m.