Triple
T3914211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I felt a Funeral, in my Brain |
E88795
|
entity |
| Predicate | punctuationFeature |
P7604
|
FINISHED |
| Object | frequent dashes |
—
|
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: frequent dashes | Statement: [I felt a Funeral, in my Brain, punctuationFeature, frequent dashes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: punctuationFeature Context triple: [I felt a Funeral, in my Brain, punctuationFeature, frequent dashes]
-
A.
punctuation
chosen
Indicates the presence, type, or pattern of punctuation marks used within or between textual elements.
-
B.
hasPunctuationSystem
Indicates that an entity possesses or employs a system of punctuation marks for structuring written language.
-
C.
titlePunctuation
Indicates that a title includes specific punctuation marks or follows a particular punctuation pattern.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
diacriticType
Indicates the specific kind or category of diacritic mark associated with a character or symbol.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.