Triple
T10291978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | warfarin |
E241385
|
entity |
| Predicate | hasTypicalINRTargetRange |
P93286
|
FINISHED |
| Object | 2.0–3.0 |
—
|
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: 2.0–3.0 | Statement: [warfarin, hasTypicalINRTargetRange, 2.0–3.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalINRTargetRange Context triple: [warfarin, hasTypicalINRTargetRange, 2.0–3.0]
-
A.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
B.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
C.
hasTypicalBeam
Indicates that an entity is associated with a characteristic or standard type of beam it commonly uses or possesses.
-
D.
usesTargetNetwork
Indicates that an entity operates or communicates through a specified target network as its underlying connection or infrastructure.
-
E.
includesRange
Indicates that one entity’s span, interval, or range fully contains or covers the span, interval, or range of another entity.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:42 a.m.