Triple
T35624281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economic Recovery Tax Act of 1981 |
E1029406
|
entity |
| Predicate | soughtToInfluence |
P30639
|
FINISHED |
| Object | labor supply |
—
|
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: labor supply | Statement: [Economic Recovery Tax Act of 1981, soughtToInfluence, labor supply]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soughtToInfluence Context triple: [Economic Recovery Tax Act of 1981, soughtToInfluence, labor supply]
-
A.
seeksToInfluence
chosen
Indicates an entity’s intention or effort to affect, shape, or alter another entity’s behavior, decisions, or state.
-
B.
politicalInfluenceIn
Indicates that an entity exerts or holds political influence within a specified place, jurisdiction, or political context.
-
C.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
D.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
E.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ef4a5f481909f3241a4e20ea37e |
completed | May 3, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.