Triple
T524120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Testify |
E10879
|
entity |
| Predicate | hasOpeningLyric |
P15282
|
FINISHED |
| Object | "The movie ran through me" |
—
|
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: "The movie ran through me" | Statement: [Testify, hasOpeningLyric, "The movie ran through me"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningLyric Context triple: [Testify, hasOpeningLyric, "The movie ran through me"]
-
A.
hasLyricsSource
Indicates that one entity serves as the source or origin of the lyrics associated with another entity.
-
B.
hasLyricsTheme
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
-
C.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
D.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
E.
hasChorus
Indicates that something (typically a song or musical piece) includes a chorus section as part of its structure.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b656c08190b387f21b06d99e68 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f018129c81909494450fcba71b59 |
completed | Feb. 28, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69a2f0f73af88190bc8f00c2047cc8b8 |
completed | Feb. 28, 2026, 1:43 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.