Triple
T36916365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marion Hammer |
E913054
|
entity |
| Predicate | lobbyingFocus |
P1876
|
FINISHED |
| Object | firearms legislation |
—
|
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: firearms legislation | Statement: [Marion Hammer, lobbyingFocus, firearms legislation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lobbyingFocus Context triple: [Marion Hammer, lobbyingFocus, firearms legislation]
-
A.
politicalInterest
Indicates that an entity has an interest, concern, or engagement in political matters, issues, or activities.
-
B.
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.
-
C.
campaignIssuesInclude
Indicates that a political campaign addresses, focuses on, or incorporates specific issues within its platform or messaging.
-
D.
hasLobbyingElement
Indicates that something includes, involves, or is associated with lobbying activities or efforts to influence decision-makers.
-
E.
hasElectoralFocus
Indicates that an entity is oriented toward, concerned with, or primarily engaged in electoral processes, campaigns, or outcomes.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55ad44bc8190a802bdaab36adc94 |
completed | May 6, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.