Triple
T9076073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernicke's aphasia |
E217486
|
entity |
| Predicate | hasSpeechFluency |
P87063
|
FINISHED |
| Object | fluent |
—
|
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: fluent | Statement: [Wernicke's aphasia, hasSpeechFluency, fluent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeechFluency Context triple: [Wernicke's aphasia, hasSpeechFluency, fluent]
-
A.
hasSpeech
Indicates that an entity produces, delivers, or is associated with a spoken utterance or verbal expression.
-
B.
hasSpeechLevels
Indicates that a language, dialect, or communicative system distinguishes different levels or styles of speech used according to social context, formality, or relative status between speakers.
-
C.
isSpoken
Indicates that a language or utterance is produced orally by a speaker or used in spoken form within a given context.
-
D.
languageCapacity
Indicates the extent to which an entity is able to understand, produce, or otherwise use language.
-
E.
isSpokenLanguage
Indicates that a language is used primarily for oral communication by speakers, as opposed to being only written or symbolic.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c53274819099b3b3047bfe8cc8 |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:12 p.m.