Triple
T37919019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralphie Tennelli |
E945902
|
entity |
| Predicate | educationalFocusOfSeries |
P6235
|
FINISHED |
| Object | science |
—
|
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: science | Statement: [Ralphie Tennelli, educationalFocusOfSeries, science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationalFocusOfSeries Context triple: [Ralphie Tennelli, educationalFocusOfSeries, science]
-
A.
educationalFocus
chosen
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
-
B.
seriesFocus
Indicates that one entity serves as the primary subject, theme, or focal point of a series created, presented, or organized by another entity.
-
C.
educationalSegment
Indicates a relationship where a segment or portion of content is specifically intended to provide instruction, learning, or educational value.
-
D.
episodeFocusOf
Indicates that a specific episode is the primary subject or focus of another entity, such as a discussion, analysis, or reference.
-
E.
educationalGenre
Indicates that one entity is categorized as an educational type or genre of content in relation to 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.