Triple
T38088856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Wife’s Relations |
E951053
|
entity |
| Predicate | hasMaritalPlot |
P19974
|
FINISHED |
| Object | man mistakenly married into a tough family |
—
|
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: man mistakenly married into a tough family | Statement: [My Wife’s Relations, hasMaritalPlot, man mistakenly married into a tough family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalPlot Context triple: [My Wife’s Relations, hasMaritalPlot, man mistakenly married into a tough family]
-
A.
hasMarriagePlot
chosen
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
B.
hasMaritalInfidelitySubplot
Indicates that the work includes a subplot involving a character engaging in romantic or sexual infidelity within a marriage.
-
C.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
D.
hasMaritalFunction
Indicates that one entity serves a role or performs a function within the context of a marital relationship or institution.
-
E.
marriageDepictedIn
Indicates that a specific marriage is represented or shown within a particular work, medium, or depiction.
- 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_69f76f03a3608190a73fd6df87c792a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:21 p.m.