Triple
T7115922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Equal Rights Amendment |
E165818
|
entity |
| Predicate | debateFocus |
P57619
|
FINISHED |
| Object | impact on existing gender-based laws |
—
|
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: impact on existing gender-based laws | Statement: [Equal Rights Amendment, debateFocus, impact on existing gender-based laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: debateFocus Context triple: [Equal Rights Amendment, debateFocus, impact on existing gender-based laws]
-
A.
fieldOfDebate
Indicates that something is the subject or domain around which a debate or argumentative discussion is centered.
-
B.
debateTopic
Indicates that one entity serves as the subject or issue being discussed or argued about in a debate involving another entity.
-
C.
mainDebateTopic
chosen
Indicates that a specified subject or issue is the primary focus or central topic of a particular debate or discussion.
-
D.
canDebate
Indicates that one entity has the ability or permission to engage in a debate or argumentative discussion with another entity.
-
E.
languageOfDebate
Indicates that a specified language is the one used for conducting a particular debate.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5f401b881909ef4c2ab1e0750db |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.