Triple
T4082726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alene Akins |
E87514
|
entity |
| Predicate | marriageSequenceWithLarryKing |
P52903
|
FINISHED |
| Object | third wife |
—
|
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: third wife | Statement: [Alene Akins, marriageSequenceWithLarryKing, third wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageSequenceWithLarryKing Context triple: [Alene Akins, marriageSequenceWithLarryKing, third wife]
-
A.
hasMarriagePlot
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
B.
marriedToNotablePerson
Indicates that a person is legally married to another individual who is widely recognized or notable.
-
C.
marriageStartWithLakihaSpicer
Indicates the point in time when a marriage involving Lakiha Spicer begins.
-
D.
marriageStartWithMilaKunis
Indicates the point in time when a marriage involving Mila Kunis begins.
-
E.
marriageStartWithMarilynMonroe
Indicates the point in time when an entity begins a marriage with Marilyn Monroe.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7933b481909bb3e02c6c04c8ee |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.