Triple
T3169905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thou Swell |
E66301
|
entity |
| Predicate | hasLyricalRegister |
P46718
|
FINISHED |
| Object | colloquial American English |
—
|
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: colloquial American English | Statement: [Thou Swell, hasLyricalRegister, colloquial American English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLyricalRegister Context triple: [Thou Swell, hasLyricalRegister, colloquial American English]
-
A.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
B.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
C.
hasVariableLyrics
Indicates that the lyrics of a song or musical piece change between different performances, versions, or contexts.
-
D.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
E.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada64917e08190bf0466d2c5e43790 |
completed | March 8, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0076b4819094628f1ad10b8f68 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada20880e481908ecac09d49b1f1c3 |
completed | March 8, 2026, 4:21 p.m. |
Created at: March 8, 2026, 3:06 p.m.