Triple
T180648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bacup |
E3866
|
entity |
| Predicate | hasIndustrialPast |
P3008
|
FINISHED |
| Object | cotton spinning |
—
|
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: cotton spinning | Statement: [Bacup, hasIndustrialPast, cotton spinning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialPast Context triple: [Bacup, hasIndustrialPast, cotton spinning]
-
A.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
B.
hasHistoricIndustry
chosen
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
C.
historicalPeakIndustrialPeriod
Indicates the time period during which an entity reached its highest level of industrial activity or development.
-
D.
historicallyUsedFor
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
-
E.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25901a9188190b8f510bec8c8e7f2 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566ccc288190add5624ede96d82b |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.