Triple
T33109407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Immanuel Bekker |
E847284
|
entity |
| Predicate | hasParticularNotation |
P4882
|
FINISHED |
| Object | Bekker numbers for Aristotle’s works |
—
|
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: Bekker numbers for Aristotle’s works | Statement: [Immanuel Bekker, hasParticularNotation, Bekker numbers for Aristotle’s works]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularNotation Context triple: [Immanuel Bekker, hasParticularNotation, Bekker numbers for Aristotle’s works]
-
A.
appearsInNotation
Indicates that one entity is represented, referenced, or depicted within the formal notation or symbolic system associated with another entity.
-
B.
hasAlternativeNotation
Indicates that an entity can be represented or written in a different, equivalent form or notation.
-
C.
hasOrnamentation
Indicates that an entity possesses decorative features or embellishments applied to its surface or structure.
-
D.
typicalNotation
chosen
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another entity.
-
E.
distinguishingNotation
Indicates that one entity uses a specific notation or symbol to distinguish or differentiate another entity from similar ones.
- 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
Created at: May 1, 2026, 1:27 a.m.