Triple
T1900732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vindolanda |
E37682
|
entity |
| Predicate | writingTabletsContent |
P33759
|
FINISHED |
| Object | military correspondence |
—
|
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: military correspondence | Statement: [Vindolanda, writingTabletsContent, military correspondence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingTabletsContent Context triple: [Vindolanda, writingTabletsContent, military correspondence]
-
A.
tabletCount
Indicates the number of tablets associated with or allocated to a given entity or context.
-
B.
tabletContentDivision
Indicates how the content displayed on a tablet device is partitioned or divided into distinct sections or regions.
-
C.
writingTool
Indicates that one entity serves as a tool or instrument used by another entity for the act of writing.
-
D.
areWrittenOn
Indicates that one entity serves as a surface or medium on which another entity is inscribed, recorded, or written.
-
E.
platforms
Indicates that one entity provides or serves as a base, medium, or environment that supports the operation, distribution, or presentation of another entity.
- 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.