Triple
T25759424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramon George Sneyd |
E648695
|
entity |
| Predicate | usedOnDocumentType |
P24327
|
FINISHED |
| Object | travel documents |
—
|
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: travel documents | Statement: [Ramon George Sneyd, usedOnDocumentType, travel documents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnDocumentType Context triple: [Ramon George Sneyd, usedOnDocumentType, travel documents]
-
A.
worksOnDocumentType
Indicates that an entity is involved in handling, processing, or performing tasks related to a specific type or category of document.
-
B.
documentTypeUsed
chosen
Indicates that a particular type or category of document is employed or applied in a given context or activity.
-
C.
belongsToDocumentType
Indicates that one entity is classified under, or associated with, a specific document type.
-
D.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
E.
DOCType
Indicates the type or category of a document associated with an entity or action.
- 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd857cfc81909fe95665d2241a72 |
completed | May 2, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 4:44 a.m.