Triple
T6772057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassidy-JLU writing system |
E155065
|
entity |
| Predicate | hasGuidelinesFor |
P18444
|
FINISHED |
| Object | word division |
—
|
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: word division | Statement: [Cassidy-JLU writing system, hasGuidelinesFor, word division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGuidelinesFor Context triple: [Cassidy-JLU writing system, hasGuidelinesFor, word division]
-
A.
hasGuidelineCount
Indicates the number of guidelines associated with or applicable to a given entity.
-
B.
hasProfessionalGuidelines
Indicates that there exist established professional rules, standards, or guidelines that govern or direct the behavior, practices, or decisions associated with the related entity.
-
C.
hasGuidelineSeries
Indicates that one entity is associated with, or belongs to, a particular series or collection of related guidelines.
-
D.
notableGuideline
Indicates that something is recognized as an important or especially significant rule, principle, or recommended practice.
-
E.
providesGuidanceTo
chosen
Indicates that one entity offers direction, advice, or instruction 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d24aaf948190a544cc28b7de67c4 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.