Triple
T25603108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Equal Rights Amendment |
E641838
|
entity |
| Predicate | aimsToProhibit |
P272
|
FINISHED |
| Object | sex-based discrimination |
—
|
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: sex-based discrimination | Statement: [Equal Rights Amendment, aimsToProhibit, sex-based discrimination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimsToProhibit Context triple: [Equal Rights Amendment, aimsToProhibit, sex-based discrimination]
-
A.
prohibits
chosen
Indicates that one entity forbids or disallows another entity from performing a specific action or being in a certain state.
-
B.
isProhibitedFor
Indicates that a certain action, object, or condition is not allowed or is forbidden for a specified entity or group.
-
C.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
D.
aimsToControl
Indicates an intention or effort by one entity to gain power over, direct, or regulate another entity or situation.
-
E.
aimsToEliminate
Indicates an intention or directed effort by one entity to remove, destroy, or completely get rid of another entity or condition.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9a89830819083b11f0b818e538d |
completed | May 2, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 4:36 p.m.