Triple
T7971892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Like the Rain |
E185341
|
entity |
| Predicate | hasRecordingYear |
P15289
|
FINISHED |
| Object | 1996 |
—
|
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: 1996 | Statement: [Like the Rain, hasRecordingYear, 1996]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecordingYear Context triple: [Like the Rain, hasRecordingYear, 1996]
-
A.
recordingYear
chosen
Indicates the specific calendar year in which something (such as audio, video, or data) was recorded.
-
B.
recordingReleaseYear
Indicates the calendar year in which a particular recording was first released to the public.
-
C.
recordStartYear
Indicates the calendar year in which a particular record, entry, or data instance first began or was created.
-
D.
hasRecordingLabel
Indicates that an entity (such as an artist or release) is associated with a particular recording label that publishes or distributes its music.
-
E.
hasRecordingWith
Indicates that one entity is associated with or includes a particular recording as part of its content or representation.
- 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd476108190988a75653a5c56d6 |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:13 p.m.