Triple
T8086162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts Department of Elder Affairs |
E188737
|
entity |
| Predicate | targetPopulationAgeGroup |
P17586
|
FINISHED |
| Object | people age 60 and older |
—
|
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: people age 60 and older | Statement: [Massachusetts Department of Elder Affairs, targetPopulationAgeGroup, people age 60 and older]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetPopulationAgeGroup Context triple: [Massachusetts Department of Elder Affairs, targetPopulationAgeGroup, people age 60 and older]
-
A.
targetedPopulation
chosen
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
B.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
C.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
D.
primarySpeakersAgeGroup
Indicates the age range category to which the main or primary speakers in a context belong.
-
E.
attractsAgeGroup
Indicates that something tends to draw interest or appeal from people belonging to a particular age group.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4160e4748190ae63624a2a03d09f |
completed | March 31, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.