Triple
T4837950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broseley |
E108106
|
entity |
| Predicate | hasLocalIndustryHeritage |
P19189
|
FINISHED |
| Object | clay tobacco pipe production |
—
|
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: clay tobacco pipe production | Statement: [Broseley, hasLocalIndustryHeritage, clay tobacco pipe production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalIndustryHeritage Context triple: [Broseley, hasLocalIndustryHeritage, clay tobacco pipe production]
-
A.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
B.
hasSmallTownIndustry
chosen
Indicates that a small town possesses or supports a particular type of industry or industrial activity.
-
C.
isPartOfHeritage
Indicates that something belongs to, contributes to, or is recognized as a component of a broader cultural, historical, or natural heritage.
-
D.
hasHeritage
Indicates that an entity possesses or is associated with a particular cultural, ethnic, or ancestral background.
-
E.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.