Triple
T33447834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Messenger |
E856554
|
entity |
| Predicate | usedInLiteratureAbout |
P136618
|
FINISHED |
| Object | Nation of Islam history |
—
|
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: Nation of Islam history | Statement: [The Messenger, usedInLiteratureAbout, Nation of Islam history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInLiteratureAbout Context triple: [The Messenger, usedInLiteratureAbout, Nation of Islam history]
-
A.
nameInLiterature
Indicates that a particular name is used or appears for an entity within a literary work or context.
-
B.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
C.
functionInLiterature
Indicates that one entity serves a particular narrative, rhetorical, or thematic role within a literary work in relation to another entity.
-
D.
usesLiteraryLens
Indicates that one entity analyzes, interprets, or evaluates another entity (such as a text or work) through a specific literary lens or critical framework.
-
E.
literaryUse
chosen
Indicates that something is employed or referenced within a literary context, such as in a written work, style, or technique.
- 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: May 1, 2026, 1:37 a.m.