Triple
T85116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fair Labor Standards Act |
E1712
|
entity |
| Predicate | coversConcept |
P1393
|
FINISHED |
| Object | nonexempt employees |
—
|
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: nonexempt employees | Statement: [Fair Labor Standards Act, coversConcept, nonexempt employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversConcept Context triple: [Fair Labor Standards Act, coversConcept, nonexempt employees]
-
A.
introducedConcept
Indicates that one entity is responsible for presenting, defining, or bringing a new concept into use or awareness for another entity or context.
-
B.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
C.
demonstratedConcept
Indicates that an entity has shown, illustrated, or made evident a particular concept through example, explanation, or action.
-
D.
coreIdea
Indicates the central concept or primary message that underlies or unifies something, such as a text, argument, or work.
-
E.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24eb59e808190811c20518f39b1cc |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.