Triple
T9791088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSX |
E237607
|
entity |
| Predicate | hasUnderlyingCompanyMainCustomerType |
P66662
|
FINISHED |
| Object | hospitals |
—
|
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: hospitals | Statement: [BSX, hasUnderlyingCompanyMainCustomerType, hospitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderlyingCompanyMainCustomerType Context triple: [BSX, hasUnderlyingCompanyMainCustomerType, hospitals]
-
A.
hasUnderlyingCompanyMainProductType
Indicates that an entity’s primary product type is based on or derived from the main product type of an associated underlying company.
-
B.
underlyingCompanyType
chosen
Indicates the classification or category of company that forms the basis or source for another related entity or instrument.
-
C.
hasParentCompanyType
Indicates that an entity is associated with a parent company of a specified organizational or business type.
-
D.
hasSecondaryCustomerType
Indicates that an entity is associated with an additional, non-primary customer classification or role.
-
E.
hasUnderlyingCompanyBusinessModel
Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda215b3108190a897552e1dc91cc4 |
completed | April 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69cd03d77c6c81909b675955bf113320 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:28 p.m.