Triple
T38021007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayla Day |
E948628
|
entity |
| Predicate | Mark DayRole |
P189866
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Kayla Day, Mark DayRole, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Mark DayRole Context triple: [Kayla Day, Mark DayRole, father]
-
A.
Matthew DayeRole
Indicates that Matthew has or performs a specific role, function, or position in relation to another entity.
-
B.
day1Name
Indicates the name or label assigned to the first day in a sequence or schedule.
-
C.
roleInMadMen
Indicates that one entity has a specific role or character in the television series "Mad Men" in relation to another entity.
-
D.
JohnnyMarksRole
Indicates that an entity has the role or professional capacity associated with Johnny Marks.
-
E.
HeathRole
Indicates a relationship where an entity holds a specific role, function, or position within a health-related context or system.
- 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:20 p.m.