Triple
T11028557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiksa Goddess |
E260695
|
entity |
| Predicate | lyricContains |
P4921
|
FINISHED |
| Object | references to Jewish family expectations |
—
|
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: references to Jewish family expectations | Statement: [Shiksa Goddess, lyricContains, references to Jewish family expectations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lyricContains Context triple: [Shiksa Goddess, lyricContains, references to Jewish family expectations]
-
A.
hasLyricsIn
Indicates that the lyrics of a work are written or available in a specified language.
-
B.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
C.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
D.
hasVariableLyrics
Indicates that the lyrics of a song or musical piece change between different performances, versions, or contexts.
-
E.
hasLyricPhrase
Indicates that one entity (typically a song or musical work) contains or is associated with a specific lyric phrase as part of its textual content.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d245a0819085135cdee9b256c5 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:25 p.m.