Triple
T33637294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RE-LY trial |
E861731
|
entity |
| Predicate | safetyEndpoint |
P179362
|
FINISHED |
| Object | major bleeding |
—
|
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: major bleeding | Statement: [RE-LY trial, safetyEndpoint, major bleeding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyEndpoint Context triple: [RE-LY trial, safetyEndpoint, major bleeding]
-
A.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related situation.
-
B.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
-
C.
safetyContext
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
-
D.
measuresSafetyUsing
Indicates that an entity evaluates or assesses safety by employing a specified method, tool, or standard.
-
E.
safetyLegacy
Indicates that an entity’s current safety status, practices, or conditions are influenced or determined by past safety decisions, standards, or incidents.
- F. None of above. chosen
Provenance (4 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f720cc1bfc8190a16118e3af8e9316 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71fb0172c81908f23e95ff16b0dec |
completed | May 3, 2026, 10:13 a.m. |
Created at: May 1, 2026, 1:42 a.m.