Triple
T31155119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeanette Juanita Ward |
E794181
|
entity |
| Predicate | spouseCharacterPlayed |
P192842
|
FINISHED |
| Object | Paul Drake |
—
|
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: Paul Drake | Statement: [Jeanette Juanita Ward, spouseCharacterPlayed, Paul Drake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseCharacterPlayed Context triple: [Jeanette Juanita Ward, spouseCharacterPlayed, Paul Drake]
-
A.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
B.
portrayedBySpouseOf
Indicates that something is portrayed or depicted by the spouse of a given entity.
-
C.
spouseOfRole
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
-
D.
spouseAppearsIn
Indicates that the spouse of a given person appears or is featured in a specified work, context, or setting.
-
E.
hasSpouseInTVSeries
Indicates that one person is the spouse of another person within the context of a specific TV series.
- F. None of above. chosen
Provenance (4 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
| PDg | Predicate description generation | batch_69fd2cf29f808190856ab1d43a51d5c7 |
completed | May 8, 2026, 12:23 a.m. |
Created at: April 29, 2026, 9:06 p.m.