Triple
T28967374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Norcross |
E732076
|
entity |
| Predicate | has focus |
P34683
|
FINISHED |
| Object | middle-class economic issues |
—
|
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: middle-class economic issues | Statement: [Donald Norcross, has focus, middle-class economic issues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has focus Context triple: [Donald Norcross, has focus, middle-class economic issues]
-
A.
hasFocusText
Indicates that one entity provides the primary or highlighted textual content associated with another entity.
-
B.
hasFocusSystem
Indicates that one entity is the primary system or subsystem that another entity is currently directing its attention, control, or processing resources toward.
-
C.
hadFocus
Indicates that an entity previously possessed or maintained primary attention, emphasis, or priority within a given context or interaction.
-
D.
haveFocusSystem
Indicates that an entity is currently the primary target or active focus within a system or context.
-
E.
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.
- 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65c2dca28819092e3a5f8e4876113 |
completed | May 2, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:52 a.m.