Triple
T15688732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yasmin Kafai |
E380267
|
entity |
| Predicate | focusesOnSetting |
P31
|
FINISHED |
| Object | schools |
—
|
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: schools | Statement: [Yasmin Kafai, focusesOnSetting, schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnSetting Context triple: [Yasmin Kafai, focusesOnSetting, schools]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
C.
focusesOnSide
Indicates that an action, attention, or analysis is directed specifically toward one particular side or aspect of something.
-
D.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
E.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:44 a.m.