Triple
T20998460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Lewis |
E517213
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Susie Lewis |
—
|
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: Susie Lewis | Statement: [Susan Lewis, hasChild, Susie Lewis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susie Lewis Context triple: [Susan Lewis, hasChild, Susie Lewis]
-
A.
Susie Lewis
chosen
Susie Lewis is an animator and producer best known for her work on the MTV animated series "Daria."
-
B.
Karen Lewis
Karen Lewis is a film and television producer known for her work on the project "Exile."
-
C.
Karen Lewis
Karen Lewis is a television producer known for her work on the British drama series "Years and Years."
-
D.
Karen Lewis
Karen Lewis is a British television producer best known for her work on acclaimed drama series such as "Last Tango in Halifax."
-
E.
Susie Sprague
Susie Sprague is an American model and actress best known for her work in glamour modeling and for her high-profile marriage to actor Corey Feldman.
- 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.