Triple
T4104720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry John Heinz |
E88421
|
entity |
| Predicate | startedFirstBusiness |
P22134
|
FINISHED |
| Object | selling bottled horseradish in clear glass jars |
—
|
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: selling bottled horseradish in clear glass jars | Statement: [Henry John Heinz, startedFirstBusiness, selling bottled horseradish in clear glass jars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startedFirstBusiness Context triple: [Henry John Heinz, startedFirstBusiness, selling bottled horseradish in clear glass jars]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
C.
hasFoundedCompany
chosen
Indicates that a person or entity has established or created a company.
-
D.
laterMainBusiness
Indicates that one business activity or enterprise occurs after and succeeds another as the main business.
-
E.
hasBusinessNode
Indicates that an entity is associated with, linked to, or represented by a specific business-related node within a business structure or network.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd31bad88190b850d1dcba14de60 |
completed | March 9, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69aef90b2ef08190ae84febfd69dd48b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:40 p.m.