Triple
T9152247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Bailey |
E219613
|
entity |
| Predicate | recordsArchiveCoverage |
P53210
|
FINISHED |
| Object | 1674–1913 |
—
|
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: 1674–1913 | Statement: [Old Bailey, recordsArchiveCoverage, 1674–1913]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordsArchiveCoverage Context triple: [Old Bailey, recordsArchiveCoverage, 1674–1913]
-
A.
archivesScope
chosen
Indicates that one entity defines or delimits the scope or coverage of another entity’s archival content or records.
-
B.
archivesHeldIn
Indicates that archival materials or records are stored, maintained, or preserved at a specified location or institution.
-
C.
archivesType
Indicates that one entity serves as an archival record or stored version of another entity, specifying the type or category of that archived content.
-
D.
archivesPeriod
Indicates that one entity serves as an archival record or repository for materials, information, or events associated with a specified time period.
-
E.
archivesModel
Indicates that one entity stores and preserves another entity as an archived model for long-term reference or retrieval.
- 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_69ca83e25418819093c6503deeaf30de |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca96cf4548190a3a45172f0e9d0ec |
completed | April 1, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:20 p.m.