Triple
T1538649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Reporter |
E32812
|
entity |
| Predicate | hasVolumeNumbering |
P3378
|
FINISHED |
| Object | sequential volumes |
—
|
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: sequential volumes | Statement: [Southern Reporter, hasVolumeNumbering, sequential volumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolumeNumbering Context triple: [Southern Reporter, hasVolumeNumbering, sequential volumes]
-
A.
hasCategoryNumbering
Indicates that an entity is assigned or associated with a specific category-based numbering or index within a classification system.
-
B.
isNumbered
Indicates that an entity has been assigned a specific number or position in an ordered sequence.
-
C.
seriesVolumeNumber
Indicates the specific volume number assigned to an item within an ordered series.
-
D.
numberingType
chosen
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
E.
numberOfVolumes
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.