Triple
T28566974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernadette Rostenkowski-Wolowitz |
E722704
|
entity |
| Predicate | marriedInEpisode |
P140690
|
FINISHED |
| Object | The Countdown Reflection |
—
|
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: The Countdown Reflection | Statement: [Bernadette Rostenkowski-Wolowitz, marriedInEpisode, The Countdown Reflection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedInEpisode Context triple: [Bernadette Rostenkowski-Wolowitz, marriedInEpisode, The Countdown Reflection]
-
A.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
-
B.
laterMarriedIn
Indicates that two entities became married at a later time relative to a previously referenced event or marital status.
-
C.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
D.
hasSpouseInTVSeries
chosen
Indicates that one person is the spouse of another person within the context of a specific TV series.
-
E.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
- 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 28, 2026, 4:07 a.m.