Triple
T38548279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mona Sterling |
E925031
|
entity |
| Predicate | isExWifeOf |
P176255
|
FINISHED |
| Object | Roger Sterling |
—
|
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: Roger Sterling | Statement: [Mona Sterling, isExWifeOf, Roger Sterling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isExWifeOf Context triple: [Mona Sterling, isExWifeOf, Roger Sterling]
-
A.
exSpouse
Indicates that two people were formerly married to each other but are no longer spouses.
-
B.
formerHusbandOf
chosen
Indicates that one person was previously the husband of another person, but the marital relationship has since ended.
-
C.
allegedSpouseOf
Indicates a relationship where one person is claimed or reported to be the spouse of another, but the marital status is not legally or definitively confirmed.
-
D.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd31521d48190adb9cbcaf4a92275 |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f81cbc8190b4fd3bfc3106c1f3 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:32 p.m.