Triple
T16667642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Equal Rights Association |
E405022
|
entity |
| Predicate | has goal |
P107402
|
FINISHED |
| Object | enfranchisement of African Americans |
—
|
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: enfranchisement of African Americans | Statement: [American Equal Rights Association, has goal, enfranchisement of African Americans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has goal Context triple: [American Equal Rights Association, has goal, enfranchisement of African Americans]
-
A.
hadGoal
chosen
Indicates that an entity previously possessed or pursued a particular goal or objective.
-
B.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or context.
-
C.
statedAsGoalFor
Indicates that something has been explicitly declared or identified as a goal for a particular entity or context.
-
D.
goalsFor
Indicates the number of goals scored by one participant or team in favor of a particular side or match context.
-
E.
laterGoal
Indicates that one goal occurs or is intended to be achieved after another goal in time.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9d9fc48190a8156c029668b544 |
completed | April 18, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.