Triple
T14891679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George C. Chapman |
E359766
|
entity |
| Predicate | studyCharacterization |
P116220
|
FINISHED |
| Object | controversial |
—
|
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: controversial | Statement: [George C. Chapman, studyCharacterization, controversial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studyCharacterization Context triple: [George C. Chapman, studyCharacterization, controversial]
-
A.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
B.
sourceCharacterization
Indicates that one entity describes, explains, or characterizes the origin, provenance, or source of another entity.
-
C.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
D.
trialCharacterization
Indicates the specific features, conditions, or parameters that define and distinguish a particular trial within an experimental or procedural context.
-
E.
findingCharacterization
Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f883288190af602633fa7d6860 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de8c1a2bcc81908f914e2e2ced65eb |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4c76e481909c0aa8d1a978e8d5 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 2:10 a.m.