Triple
T28365776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancaster slave trade |
E718481
|
entity |
| Predicate | benefitedIndustry |
P32550
|
FINISHED |
| Object | shipbuilding in Lancaster |
—
|
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: shipbuilding in Lancaster | Statement: [Lancaster slave trade, benefitedIndustry, shipbuilding in Lancaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitedIndustry Context triple: [Lancaster slave trade, benefitedIndustry, shipbuilding in Lancaster]
-
A.
sectorBenefited
chosen
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
-
B.
supportedIndustry
Indicates that one entity provides backing, resources, or services to help sustain or advance a particular industry.
-
C.
impactOnIndustry
Indicates the effect or influence that one entity, event, or action has on the state, performance, or development of an industry.
-
D.
benefitedCountry
Indicates that one country gains an advantage, profit, or positive outcome from an action, event, or entity associated with another.
-
E.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 12:54 a.m.