Triple
T2175846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Memory of Solferino |
E48525
|
entity |
| Predicate | secondPartSubject |
P37646
|
FINISHED |
| Object | analysis of the need for relief societies |
—
|
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: analysis of the need for relief societies | Statement: [A Memory of Solferino, secondPartSubject, analysis of the need for relief societies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPartSubject Context triple: [A Memory of Solferino, secondPartSubject, analysis of the need for relief societies]
-
A.
secondPartTitle
Indicates that one entity is the second part of the title of another entity.
-
B.
secondPartFocus
Indicates that the communicative or informational focus is placed on the second part or element in a two-part structure or relation.
-
C.
secondaryTo
Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
-
D.
secondPartFormat
Indicates that the entity represents the format or structure of the second part or segment of a larger item or sequence.
-
E.
secondWord
Indicates that one entity is the second word in sequence immediately following the first entity in a text or utterance.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc434978c8190b9c4dd8411b87f23 |
completed | March 7, 2026, 6:22 a.m. |
Created at: March 4, 2026, 7:45 p.m.