Triple
T25747690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darlene Conner |
E648385
|
entity |
| Predicate | ageGroupAtSeriesStart |
P125218
|
FINISHED |
| Object | teenager |
—
|
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: teenager | Statement: [Darlene Conner, ageGroupAtSeriesStart, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupAtSeriesStart Context triple: [Darlene Conner, ageGroupAtSeriesStart, teenager]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
C.
ageGroupIndicated
chosen
Indicates that a specific age range or category is identified or assigned to an entity.
-
D.
ageGroupStructure
Indicates how a population or set of entities is distributed across different age groups or age categories.
-
E.
ageAtIntroduction
Indicates the age an entity had at the time it was first introduced or presented in a given context.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd2075f48190926b27fd068fb371 |
completed | May 2, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 3:53 a.m.