Triple
T36128810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellow Belt |
E1044957
|
entity |
| Predicate | knowledgeDepth |
P184728
|
FINISHED |
| Object | introductory |
—
|
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: introductory | Statement: [Yellow Belt, knowledgeDepth, introductory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knowledgeDepth Context triple: [Yellow Belt, knowledgeDepth, introductory]
-
A.
knowledgeScope
Indicates the extent or range of information, topics, or understanding that an entity possesses or is concerned with.
-
B.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
C.
knowledgeLevelAssessed
Indicates that an entity’s level of knowledge or understanding has been evaluated or measured, typically against some criteria or standard.
-
D.
knowledge
Indicates that one entity possesses information, understanding, or awareness about another entity, concept, or fact.
-
E.
knowledgeTypeRecorded
Indicates that the specific type or category of knowledge associated with an entity has been documented or stored.
- F. None of above. chosen
Provenance (4 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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b3e0f1c88190985feab6cee8b05e |
completed | May 3, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:08 p.m.