Triple
T1901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Science Foundation |
E35
|
entity |
| Predicate | excludesField |
P153
|
FINISHED |
| Object | medical research |
—
|
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: medical research | Statement: [National Science Foundation, excludesField, medical research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: excludesField Context triple: [National Science Foundation, excludesField, medical research]
-
A.
eligibility
Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
-
B.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
E.
requires
Indicates that one entity must exist, occur, or be satisfied before another entity can exist, occur, or be carried out.
- 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_69a22cde80848190b62c5f556b4d62ba |
completed | Feb. 27, 2026, 11:46 p.m. |
| NER | Named-entity recognition | batch_69a2316d88a08190b2e03041674b5674 |
completed | Feb. 28, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69a230c3ee4481908216244c38aa8aef |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a2316cbe58819096cc036d6e3b103c |
completed | Feb. 28, 2026, 12:06 a.m. |
Created at: Feb. 27, 2026, 11:48 p.m.