Triple
T18391352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-Neck Records |
E449734
|
entity |
| Predicate | notableRelease |
P13405
|
FINISHED |
| Object | Harvest for the World |
—
|
NE NERFINISHED |
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: Harvest for the World | Statement: [T-Neck Records, notableRelease, Harvest for the World]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harvest for the World Context triple: [T-Neck Records, notableRelease, Harvest for the World]
-
A.
Harvest for the World
chosen
"Harvest for the World" is a socially conscious soul/R&B song by The Isley Brothers that calls for global peace, unity, and compassion.
-
B.
Harvest
Harvest is a 1972 folk-rock album by Neil Young, widely regarded as one of his signature works and a classic of the singer-songwriter era.
-
C.
Harvest
"Harvest" is a medical thriller novel by Tess Gerritsen that follows a young surgical resident who uncovers a deadly black-market organ trafficking scheme.
-
D.
The Harvest
The Harvest is a landscape painting by French Barbizon school artist Charles-François Daubigny, depicting rural agricultural life with his characteristic naturalistic light and atmosphere.
-
E.
The Harvest
The Harvest is an Impressionist painting by Camille Pissarro depicting rural agricultural laborers working in the fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e518422e488190bd06fad72efa1641 |
completed | April 19, 2026, 6 p.m. |
Created at: April 10, 2026, 10:46 a.m.