Triple
T108495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capital Magnet Fund |
E2190
|
entity |
| Predicate | targetAreas |
P481
|
FINISHED |
| Object | economically distressed communities |
—
|
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: economically distressed communities | Statement: [Capital Magnet Fund, targetAreas, economically distressed communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAreas Context triple: [Capital Magnet Fund, targetAreas, economically distressed communities]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
C.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
D.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
E.
targetMarket
chosen
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25a1199ac8190ac65ffaaf45b4f5b |
completed | Feb. 28, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69a2563e7188819091e9a94e071991d7 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.