Triple
T1900731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vindolanda |
E37682
|
entity |
| Predicate | writingTabletsSignificance |
P33758
|
FINISHED |
| Object | earliest known handwritten documents from Britain |
—
|
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: earliest known handwritten documents from Britain | Statement: [Vindolanda, writingTabletsSignificance, earliest known handwritten documents from Britain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingTabletsSignificance Context triple: [Vindolanda, writingTabletsSignificance, earliest known handwritten documents from Britain]
-
A.
tabletCount
Indicates the number of tablets associated with or allocated to a given entity or context.
-
B.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
-
C.
tabletContentDivision
Indicates how the content displayed on a tablet device is partitioned or divided into distinct sections or regions.
-
D.
displays
Indicates that one entity visually presents or shows another entity’s content or information.
-
E.
hardwareUsedBy
Indicates that a piece of hardware is utilized or operated by a particular entity (such as a person, system, or organization).
- F. None of above. chosen
Provenance (4 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb34c4a64819096e12b152b84c334 |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:35 p.m.