Triple
T19663769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Of the Farm |
E472148
|
entity |
| Predicate | hasProtagonistMaritalStatus |
P105779
|
FINISHED |
| Object | remarried man |
—
|
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: remarried man | Statement: [Of the Farm, hasProtagonistMaritalStatus, remarried man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistMaritalStatus Context triple: [Of the Farm, hasProtagonistMaritalStatus, remarried man]
-
A.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
B.
hasCivilStatus
chosen
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
C.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
D.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
E.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416671fc81908e25b0477234fa0f |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.