Triple
T12084788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugh Franklin |
E287777
|
entity |
| Predicate | typeOfMilitancy |
P103414
|
FINISHED |
| Object | direct action in support of women's suffrage |
—
|
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: direct action in support of women's suffrage | Statement: [Hugh Franklin, typeOfMilitancy, direct action in support of women's suffrage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMilitancy Context triple: [Hugh Franklin, typeOfMilitancy, direct action in support of women's suffrage]
-
A.
endedInsurgencyType
Indicates the specific manner or category of outcome by which an insurgency was brought to an end.
-
B.
typeOfTerrorism
Indicates a classification relationship where an act or event is identified as belonging to a specific category or type of terrorism.
-
C.
wasMilitarized
Indicates that an entity underwent a process of being organized, equipped, or adapted for military use or purposes.
-
D.
isMilitarized
Indicates that an entity is organized, equipped, or structured according to military principles, forces, or purposes.
-
E.
violenceLevel
Indicates the degree or intensity of violent behavior, actions, or content present in or associated with an 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9178814e081908f67e3846718530e |
completed | April 10, 2026, 3:30 p.m. |
Created at: April 8, 2026, 9:48 p.m.