Triple
T11604182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahanoy City, Pennsylvania |
E275210
|
entity |
| Predicate | hasEconomicTrend |
P7393
|
FINISHED |
| Object | post-industrial economic decline |
—
|
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: post-industrial economic decline | Statement: [Mahanoy City, Pennsylvania, hasEconomicTrend, post-industrial economic decline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicTrend Context triple: [Mahanoy City, Pennsylvania, hasEconomicTrend, post-industrial economic decline]
-
A.
economicTrend
chosen
Indicates the general direction or pattern of economic activity or conditions over a period of time.
-
B.
hasEconomicFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in economic matters, activities, or impacts.
-
C.
hasEconomicShift
Indicates a change in the economic state, structure, or conditions affecting an entity over time.
-
D.
hasEconomicContext
Indicates that something is associated with, influenced by, or situated within a particular economic situation, condition, or set of financial circumstances.
-
E.
hasEconomicDimension
Indicates that something involves, affects, or is characterized by economic factors, considerations, or consequences.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d895502e0081909ee9c3d45d26cd91 |
completed | April 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.