Triple
T6966498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin Cover |
E161501
|
entity |
| Predicate | portrayedInterracialMarriage |
P55095
|
FINISHED |
| Object | on The Jeffersons |
—
|
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: on The Jeffersons | Statement: [Franklin Cover, portrayedInterracialMarriage, on The Jeffersons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedInterracialMarriage Context triple: [Franklin Cover, portrayedInterracialMarriage, on The Jeffersons]
-
A.
featuresInterracialCasting
chosen
Indicates that the work includes casting choices where performers of different racial backgrounds appear together in significant roles or interactions.
-
B.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
C.
portrayedBySpouseOf
Indicates that something is portrayed or depicted by the spouse of a given entity.
-
D.
marriageCharacterization
Indicates how a marriage is described, evaluated, or characterized in terms of its qualities, dynamics, or nature.
-
E.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
- 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.