Triple
T19773658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takeda Pharmaceutical Company |
E474950
|
entity |
| Predicate | hasNotableProductArea |
P79108
|
FINISHED |
| Object | cancer treatments |
—
|
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: cancer treatments | Statement: [Takeda Pharmaceutical Company, hasNotableProductArea, cancer treatments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProductArea Context triple: [Takeda Pharmaceutical Company, hasNotableProductArea, cancer treatments]
-
A.
hasNotableCompany
Indicates that an entity is associated with or linked to a company that is considered notable or significant in some context.
-
B.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
C.
hasNotableInnovation
Indicates that an entity is associated with a significant, distinguishing innovation or breakthrough.
-
D.
hasNotableProject
Indicates that an entity is associated with a project that is distinguished or recognized as significant in some way.
-
E.
hasNotabilityCategory
chosen
Indicates that an entity is associated with a particular category that characterizes its type or area of notability.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535e450c8190a2628245ae0d0bd3 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.