Triple
T3579728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alva Erskine Vanderbilt |
E75769
|
entity |
| Predicate | genreOfActivism |
P11461
|
FINISHED |
| Object | 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: women’s suffrage | Statement: [Alva Erskine Vanderbilt, genreOfActivism, women’s suffrage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfActivism Context triple: [Alva Erskine Vanderbilt, genreOfActivism, women’s suffrage]
-
A.
genreOfPoliticalActivity
Indicates the specific type or category of political activity that characterizes or classifies a given political action or engagement.
-
B.
areaOfActivism
chosen
Indicates the specific social, political, or environmental cause or issue that an entity actively advocates for or works to change.
-
C.
placeOfActivism
Indicates the location or geographic area where an individual or group engages in activism or advocacy activities.
-
D.
genreOfPhilanthropy
Indicates the specific type or category of philanthropic activity to which an act, initiative, or organization belongs.
-
E.
activityType
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0ffecdc8190bf01c8ba90e3733e |
completed | March 8, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.