Triple
T20877592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer Doug Penhall |
E514059
|
entity |
| Predicate | hasAgeGroupDepicted |
P13483
|
FINISHED |
| Object | young adult |
—
|
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: young adult | Statement: [Officer Doug Penhall, hasAgeGroupDepicted, young adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeGroupDepicted Context triple: [Officer Doug Penhall, hasAgeGroupDepicted, young adult]
-
A.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
B.
ageGroupIndicated
Indicates that a specific age range or category is identified or assigned to an entity.
-
C.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
intendedForAgeGroup
Indicates that something is designed, suitable, or targeted for use by a specific age group.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6767ec0819080721e2e75bd0d66 |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.