Triple
T195387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biogen |
E3807
|
entity |
| Predicate | hasKeyTherapeuticArea |
P466
|
FINISHED |
| Object | multiple sclerosis |
—
|
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: multiple sclerosis | Statement: [Biogen, hasKeyTherapeuticArea, multiple sclerosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyTherapeuticArea Context triple: [Biogen, hasKeyTherapeuticArea, multiple sclerosis]
-
A.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
hasKeyActivity
Indicates that an entity is associated with or performs a primary or central activity.
-
D.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
-
E.
hasKeyFigure
Indicates that an entity includes, involves, or is characterized by an important or central person relevant to it.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25969425081908e178db8ba4631c2 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25677da14819094cd02868fd30c83 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.