Triple
T27741841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | laborInfluence |
P134586
|
FINISHED |
| Object | strong public sector unions |
—
|
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: strong public sector unions | Statement: [New Jersey politics, laborInfluence, strong public sector unions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laborInfluence Context triple: [New Jersey politics, laborInfluence, strong public sector unions]
-
A.
laborPolicy
Indicates a relationship where an authority or organization defines, regulates, or enforces rules and standards governing labor conditions, rights, and practices.
-
B.
laborProvisionEffect
Indicates the impact or consequences that providing labor has on another entity, condition, or outcome.
-
C.
laborUnion
Indicates that an entity is a labor union representing workers in collective employment-related matters.
-
D.
labour
Indicates that an entity performs work or exerts effort, typically in a productive, economic, or physical context, often for another entity or purpose.
-
E.
laborMarketEffect
chosen
Indicates the impact that an action, policy, or condition has on employment, wages, or other labor market 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 4:11 p.m.