Triple
T20998032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Dix |
E517201
|
entity |
| Predicate | spouseOf |
P13
|
FINISHED |
| Object | Martha Dix |
—
|
NE NERFINISHED |
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: Martha Dix | Statement: [Otto Dix, spouseOf, Martha Dix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha Dix Context triple: [Otto Dix, spouseOf, Martha Dix]
-
A.
Martha Dix
chosen
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
B.
Martha Hudson
Martha Hudson is an American sprinter who was one of the top female track athletes of her era, notably competing internationally under coach Ed Temple at Tennessee State University.
-
C.
Martha Hunt
Martha Hunt is an American fashion model best known for her work with Victoria’s Secret, including serving as a Victoria’s Secret Angel.
-
D.
Martha McKay
Martha McKay is a fictional character in the 2015 romantic action-comedy film "Mr. Right."
-
E.
Martha Williamson
Martha Williamson is an American television producer and writer best known for developing and leading the hit inspirational drama series "Touched by an Angel."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc22ca6081908bf054ddcfea9e19 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:51 p.m.