Triple
T9807193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xeloda |
E238181
|
entity |
| Predicate | isTeratogenic |
P6478
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Xeloda, isTeratogenic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTeratogenic Context triple: [Xeloda, isTeratogenic, true]
-
A.
notableToxicity
Indicates that an entity is recognized for having a significant level or history of toxicity, harm, or detrimental effects in its context or interactions.
-
B.
toxicTo
chosen
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
C.
embryologicalFeature
Indicates a relationship where one entity is an anatomical or biological structure characterized or defined by its origin, development, or properties during the embryonic stage.
-
D.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
E.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7cb9588190953a063cb7b9e29e |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.