Triple
T11074762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLEOPATRA trial |
E261834
|
entity |
| Predicate | controlArmTreatment |
P97060
|
FINISHED |
| Object | trastuzumab plus docetaxel |
—
|
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: trastuzumab plus docetaxel | Statement: [CLEOPATRA trial, controlArmTreatment, trastuzumab plus docetaxel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlArmTreatment Context triple: [CLEOPATRA trial, controlArmTreatment, trastuzumab plus docetaxel]
-
A.
armsControl
Indicates a relationship where parties engage in limiting, regulating, or reducing weapons and military capabilities, often through agreements or treaties.
-
B.
hasArm
Indicates that one entity possesses or is equipped with an arm as a physical part or component of itself.
-
C.
armType
Indicates the specific kind or configuration of an arm associated with an entity.
-
D.
controlMethods
Indicates the methods or techniques used by one entity to direct, regulate, or influence the behavior, operation, or state of another entity.
-
E.
laterArm
Indicates that one event, state, or action occurs at a later time than another within the same arm or branch of a process or study.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7994efb608190a81bc8c4d16ddbd0 |
completed | April 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69d74415403c81909778bcd829e8832e |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:26 p.m.