Triple
T33556306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mission Song |
E859484
|
entity |
| Predicate | hasEthnicBackgroundOfProtagonist |
P28254
|
FINISHED |
| Object | Congolese |
—
|
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: Congolese | Statement: [The Mission Song, hasEthnicBackgroundOfProtagonist, Congolese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicBackgroundOfProtagonist Context triple: [The Mission Song, hasEthnicBackgroundOfProtagonist, Congolese]
-
A.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
B.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
C.
hasEthnicOrRegionalOrigin
Indicates that an entity originates from, or is associated with, a particular ethnic group or geographic region.
-
D.
hasBiographicalSubjectEthnicity
Indicates that the biographical subject is associated with a specific ethnicity.
-
E.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character of, another entity.
- 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_69f3497b2b68819093207971b5e13dc8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 1, 2026, 1:40 a.m.