Triple
T16450976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kauffman |
E399547
|
entity |
| Predicate | hasNotableAssociatedIndustry |
P110684
|
FINISHED |
| Object | pharmaceutical industry |
—
|
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: pharmaceutical industry | Statement: [Kauffman, hasNotableAssociatedIndustry, pharmaceutical industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAssociatedIndustry Context triple: [Kauffman, hasNotableAssociatedIndustry, pharmaceutical industry]
-
A.
hasFoundingIndustryAssociation
Indicates that an entity is associated with an industry organization that played a role in its founding or establishment.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
hasIndustryTies
chosen
Indicates that an entity maintains professional, financial, or organizational connections with a particular industry or sector.
-
D.
hasNotableCompany
Indicates that an entity is associated with or linked to a company that is considered notable or significant in some context.
-
E.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ce06de0819086eea241c6b32223 |
completed | April 18, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:10 a.m.