Triple
T31163531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elaine Harper |
E794406
|
entity |
| Predicate | hasFiance |
P97856
|
FINISHED |
| Object | Mortimer Brewster |
—
|
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: Mortimer Brewster | Statement: [Elaine Harper, hasFiance, Mortimer Brewster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFiance Context triple: [Elaine Harper, hasFiance, Mortimer Brewster]
-
A.
isFianceeOf
chosen
Indicates that one person is the engaged-to-be-married partner of another person.
-
B.
hasFianceeOfSonAsLover
Indicates that a person is in a romantic or sexual relationship with their son’s fiancée.
-
C.
hasDoubleOfHusband
Indicates that one person is married to another man who is a double or duplicate (e.g., look-alike or counterpart) of a specified husband.
-
D.
isMarriedToA
Indicates that one entity is legally and socially bound in marriage to another specific entity.
-
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_69f224d504908190b01278dcb7fc3fa7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: April 29, 2026, 9:07 p.m.