Triple
T4746138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadstairs |
E105362
|
entity |
| Predicate | hasProminentIndustry |
P13800
|
FINISHED |
| Object | tourism |
—
|
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: tourism | Statement: [Broadstairs, hasProminentIndustry, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProminentIndustry Context triple: [Broadstairs, hasProminentIndustry, tourism]
-
A.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
notableIndustry
chosen
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
- 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64ab946481909eccdb3e8c5d1f6a |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.