Triple
T31974384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bachelor Father |
E816408
|
entity |
| Predicate | nieceCharacterRole |
P173070
|
FINISHED |
| Object | Noreen Corcoran as Kelly Gregg |
—
|
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: Noreen Corcoran as Kelly Gregg | Statement: [Bachelor Father, nieceCharacterRole, Noreen Corcoran as Kelly Gregg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nieceCharacterRole Context triple: [Bachelor Father, nieceCharacterRole, Noreen Corcoran as Kelly Gregg]
-
A.
niece
Indicates that one person is the female child of another person's sibling or sibling-in-law.
-
B.
nieceOrNephewOf
Indicates that one person is the niece or nephew (the child of a sibling or sibling-in-law) of another person.
-
C.
auntCharacterRole
Indicates that one character has the familial role of aunt in relation to another character.
-
D.
spouseOfNieceOf
Indicates a relationship where one person is the spouse (husband or wife) of another person's niece.
-
E.
childOfCharacter
Indicates that one character is the offspring (biological, adopted, or otherwise recognized child) of another character.
- F. None of above. chosen
Provenance (4 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b343b8948190993241cef00000dd |
completed | May 3, 2026, 2:30 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:11 a.m.