Triple
T12270757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | partial-birth abortion |
E292463
|
entity |
| Predicate | hasMedicalName |
P94429
|
FINISHED |
| Object | intact dilation and extraction |
—
|
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: intact dilation and extraction | Statement: [partial-birth abortion, hasMedicalName, intact dilation and extraction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalName Context triple: [partial-birth abortion, hasMedicalName, intact dilation and extraction]
-
A.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
B.
hasNameGivenTo
chosen
Indicates that one entity is the name that has been assigned or given to another entity.
-
C.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
D.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
E.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.