Triple
T6966311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Jefferson |
E161496
|
entity |
| Predicate | ethnicityInFiction |
P28254
|
FINISHED |
| Object | African-American |
—
|
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: African-American | Statement: [Louise Jefferson, ethnicityInFiction, African-American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicityInFiction Context triple: [Louise Jefferson, ethnicityInFiction, African-American]
-
A.
fictionalEthnoCulturalIdentity
Indicates that an entity is associated with an invented or imaginary ethnic or cultural identity, rather than a real-world one.
-
B.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
C.
nationalityInMyth
Indicates that a mythological figure, character, or entity is associated with a particular nationality or cultural tradition within mythology.
-
D.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
E.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db121174819098e73e45f6c9cc91 |
completed | March 27, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.