Triple
T19539571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas P. Lowry |
E488858
|
entity |
| Predicate | typeOfHistorian |
P17033
|
FINISHED |
| Object | social historian of the Civil War |
—
|
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: social historian of the Civil War | Statement: [Thomas P. Lowry, typeOfHistorian, social historian of the Civil War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHistorian Context triple: [Thomas P. Lowry, typeOfHistorian, social historian of the Civil War]
-
A.
historianAuthor
Indicates that one entity is the historian who authored or wrote the work represented by the other entity.
-
B.
historian
chosen
Indicates that an entity studies, interprets, or writes about past events or historical subjects in relation to another entity.
-
C.
historianDescribing
Indicates that a historian is providing an account, explanation, or interpretation of a subject, event, or entity.
-
D.
historicalType
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
E.
historicalFigureTypeCovered
Indicates that a given type or category of historical figure is included or addressed within a particular context, work, or dataset.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63871d00881909ed7371ae5577957 |
completed | April 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.