Triple
T2790372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerry Connolly |
E61913
|
entity |
| Predicate | hasWorkFocus |
P34683
|
FINISHED |
| Object | federal workforce protections |
—
|
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: federal workforce protections | Statement: [Gerry Connolly, hasWorkFocus, federal workforce protections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkFocus Context triple: [Gerry Connolly, hasWorkFocus, federal workforce protections]
-
A.
hasWorkBy
Indicates that one entity (such as a collection, exhibition, or publication) includes or contains creative works produced by another entity (such as an artist, author, or creator).
-
B.
hasWorkSubject
Indicates that a work (such as a document, artwork, or project) is about or concerns a particular subject or topic.
-
C.
hasWorkAsSubject
Indicates that an entity serves as the subject (creator or originator) of a particular work or creative output.
-
D.
hasProgramFocus
chosen
Indicates that an entity (such as a program or initiative) is oriented around or primarily concerned with a particular thematic area, topic, or objective.
-
E.
hasWorkCount
Indicates the number of works (such as items, creations, or outputs) associated with a given entity.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:58 p.m.