Triple
T29435465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Wolff |
E746559
|
entity |
| Predicate | neurotype |
P167171
|
FINISHED |
| Object | autistic traits |
—
|
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: autistic traits | Statement: [Christian Wolff, neurotype, autistic traits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neurotype Context triple: [Christian Wolff, neurotype, autistic traits]
-
A.
isNeutral
Indicates that an entity maintains a balanced, unbiased, or non-aligned stance with respect to other entities, options, or conflicting sides.
-
B.
usesNeutral
Indicates that one entity employs or applies something in a neutral, unbiased, or non-aligned manner toward another entity or context.
-
C.
personalityType
Indicates the specific psychological or behavioral profile that characterizes an entity’s typical patterns of thinking, feeling, and acting.
-
D.
pathotype
Indicates the specific pattern or type of pathogenic behavior or disease-causing capability exhibited by an organism relative to its host.
-
E.
isToneNeutral
Indicates that the tone of the referenced content is neither positive nor negative, but emotionally neutral or unbiased.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66accf77c81908f0f4c1a67e05e47 |
completed | May 2, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 3:16 p.m.