Triple
T7149302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reeves v. Sanderson Plumbing Products, Inc. |
E166649
|
entity |
| Predicate | employeeAgeGroup |
P19123
|
FINISHED |
| Object | over 40 |
—
|
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: over 40 | Statement: [Reeves v. Sanderson Plumbing Products, Inc., employeeAgeGroup, over 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employeeAgeGroup Context triple: [Reeves v. Sanderson Plumbing Products, Inc., employeeAgeGroup, over 40]
-
A.
ageGroup
chosen
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
C.
ageGroupRole
Indicates the role or function an entity has within a specific age group classification.
-
D.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
E.
ageGroupStructure
Indicates how a population or set of entities is distributed across different age groups or age categories.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7f130e08190bc5ca99f90f9de92 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.