Triple
T8504351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally Gardner |
E201295
|
entity |
| Predicate | writesForAgeGroup |
P54225
|
FINISHED |
| Object | children |
—
|
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: children | Statement: [Sally Gardner, writesForAgeGroup, children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writesForAgeGroup Context triple: [Sally Gardner, writesForAgeGroup, children]
-
A.
writesForAudience
chosen
Indicates that an agent creates written content intended specifically for a particular audience or readership.
-
B.
performedForAgeGroup
Indicates that an action or performance is specifically intended for, targeted at, or carried out on behalf of a particular age group.
-
C.
writtenByAtAge
Indicates that something was written by a particular entity when that entity was a specified age.
-
D.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
E.
willWrittenIn
Indicates that a legal will was authored, drafted, or formally written in a specified location or jurisdiction.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe59d67d081908155a43b9b463fe3 |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:14 p.m.