Triple
T3873129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humana |
E92432
|
entity |
| Predicate | hasMainProduct |
P7216
|
FINISHED |
| Object | health insurance policies |
—
|
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: health insurance policies | Statement: [Humana, hasMainProduct, health insurance policies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainProduct Context triple: [Humana, hasMainProduct, health insurance policies]
-
A.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
-
B.
hasMainOrgan
Indicates that an entity possesses a primary or principal organ that plays a central role in its biological or functional system.
-
C.
hasMainSite
Indicates that one entity is designated as the primary or central site associated with another entity.
-
D.
primaryProduct
chosen
Indicates that one entity is the main or most important product associated with, produced by, or offered by another entity.
-
E.
hasMainHost
Indicates that one entity serves as the primary or principal host for another entity.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.