Triple
T13932145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6 Feet Deep |
E335018
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Poetic |
E335016
|
NE 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: Poetic | Statement: [6 Feet Deep, producer, Poetic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poetic Context triple: [6 Feet Deep, producer, Poetic]
-
A.
Poetic
chosen
Poetic was an American rapper best known as a member of the influential horrorcore group Gravediggaz.
-
B.
Abstract Poetic
Abstract Poetic is the former stage name of Kamaal Ibn John Fareed, better known as Q-Tip, the influential rapper, producer, and member of A Tribe Called Quest.
-
C.
Dialectical Lyric
Dialectical Lyric is a philosophical-literary work by Søren Kierkegaard (under the pseudonym Johannes de Silentio) that blends lyrical reflection with dialectical exploration of existential themes.
-
D.
Poems, Dramatic and Lyrical
Poems, Dramatic and Lyrical is a collection of verse by English poet Frederick Tennyson that showcases his blend of dramatic narrative and lyrical expression.
-
E.
Poetry
Poetry is a Python dependency management and packaging tool that simplifies creating, building, and publishing Python projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1c67e2c8190a14b273af0d93b0a |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:16 p.m.