Triple
T11300937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Leland |
E267582
|
entity |
| Predicate | advocacy focus |
P1876
|
FINISHED |
| Object | food security |
—
|
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: food security | Statement: [Mickey Leland, advocacy focus, food security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advocacy focus Context triple: [Mickey Leland, advocacy focus, food security]
-
A.
advocatesAgainst
Indicates that one entity actively opposes, argues against, or campaigns to prevent or stop another entity, action, or idea.
-
B.
advocacyOrganization
Indicates that an organization actively supports, promotes, or works on behalf of a cause, issue, or group through advocacy activities.
-
C.
advocates
Indicates that one entity publicly supports, recommends, or argues in favor of another entity or its interests.
-
D.
policyFocus
chosen
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
E.
emphasizesPolicyArea
Indicates that one entity gives particular importance or priority to a specific policy area in its actions, statements, or focus.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a4aad4819097384e1b591be2e3 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.