Triple
T30464905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uncle Rat |
E775107
|
entity |
| Predicate | ageGroupPortrayal |
P13483
|
FINISHED |
| Object | adult male relative |
—
|
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: adult male relative | Statement: [Uncle Rat, ageGroupPortrayal, adult male relative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupPortrayal Context triple: [Uncle Rat, ageGroupPortrayal, adult male relative]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
C.
ageGroupStructure
Indicates how a population or set of entities is distributed across different age groups or age categories.
-
D.
ageGroupIndicated
Indicates that a specific age range or category is identified or assigned to an entity.
-
E.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
- 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_69f2249622a48190b1fae2e3e4ee958a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f686f314fc81908a65eec389e8b1fb |
completed | May 2, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:11 p.m.