Triple
T32196017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | folinic acid |
E822405
|
entity |
| Predicate | antidoteFor |
P4524
|
FINISHED |
| Object | methotrexate |
—
|
NE NERFINISHED |
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: methotrexate | Statement: [folinic acid, antidoteFor, methotrexate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antidoteFor Context triple: [folinic acid, antidoteFor, methotrexate]
-
A.
hasAntivenom
Indicates that an entity possesses or provides an antivenom specifically effective against another entity’s venom.
-
B.
remedy
chosen
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
-
C.
opposesEffectOf
Indicates that one entity counteracts, reduces, or nullifies the effect produced by another entity.
-
D.
isTypicallyNeutralizedWith
Indicates that something is commonly counteracted, rendered harmless, or balanced by another specified thing.
-
E.
moreResistantToPoisoningThan
Indicates that one entity has a higher resistance or tolerance to poisoning than another entity.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb3795fc8190bfcb00d45aa887a1 |
completed | May 3, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.