Triple
T11884056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merchant (The Canterbury Tales) |
E282730
|
entity |
| Predicate | spouseDescription |
P91240
|
FINISHED |
| Object | shrewish 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: shrewish wife | Statement: [Merchant (The Canterbury Tales), spouseDescription, shrewish wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseDescription Context triple: [Merchant (The Canterbury Tales), spouseDescription, shrewish wife]
-
A.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
B.
hasSpouseDescribed
Indicates that one entity is described as the spouse of another entity.
-
C.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouseCharacteristic
chosen
Indicates that a particular characteristic, trait, or attribute is associated with a person’s spouse within the relationship.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a02ad4819090faef0e0be732ee |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.