Triple
T6714040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahoning Valley |
E153217
|
entity |
| Predicate | hasEconomicHistoryEvent |
P2107
|
FINISHED |
| Object | decline of steel industry in the 1970s |
—
|
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: decline of steel industry in the 1970s | Statement: [Mahoning Valley, hasEconomicHistoryEvent, decline of steel industry in the 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicHistoryEvent Context triple: [Mahoning Valley, hasEconomicHistoryEvent, decline of steel industry in the 1970s]
-
A.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
B.
historicalEconomicBase
Indicates the primary type of economic activity or production that historically underpinned or sustained an entity’s economy.
-
C.
hasEconomicContext
Indicates that something is associated with, influenced by, or situated within a particular economic situation, condition, or set of financial circumstances.
-
D.
historicalImpact
Indicates the influence or lasting effects that an entity, event, or action has had on subsequent history or historical developments.
-
E.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d122d6cc81909bde0c94fb95f016 |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:07 p.m.