Triple
T9181543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Yvain |
E220341
|
entity |
| Predicate | symbolicAttribute |
P64550
|
FINISHED |
| Object | lion as emblem of courage and loyalty |
—
|
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: lion as emblem of courage and loyalty | Statement: [Sir Yvain, symbolicAttribute, lion as emblem of courage and loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolicAttribute Context triple: [Sir Yvain, symbolicAttribute, lion as emblem of courage and loyalty]
-
A.
symbolicAspect
chosen
Indicates that one entity functions as a symbol or emblem that represents, expresses, or conveys a particular meaning, quality, or concept of another entity.
-
B.
attributeType
Indicates that one entity specifies the kind or category of attribute that characterizes another entity.
-
C.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
D.
representedByAttribute
Indicates that one entity serves as an attribute-based representation or characterization of another entity.
-
E.
symbolicAbility
Indicates the capacity of an entity to understand, manipulate, or use symbols to represent concepts, objects, or relationships.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc25379008190b8ca047efe3bb7bb |
completed | April 1, 2026, 6:59 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.