Triple
T23839647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ritual Fragment |
E590948
|
entity |
| Predicate | hasAbstractCharacter |
P153831
|
FINISHED |
| Object | ritualistic |
—
|
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: ritualistic | Statement: [Ritual Fragment, hasAbstractCharacter, ritualistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAbstractCharacter Context triple: [Ritual Fragment, hasAbstractCharacter, ritualistic]
-
A.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
B.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
C.
hasCharacterClass
Indicates that an entity (such as a character) belongs to or is assigned a particular character class or role type.
-
D.
hasImaginaryCharacter
Indicates that an entity includes, features, or is associated with a fictional or imaginary character.
-
E.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c886aab081909ad896abe383afb9 |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f158b0e320819090b947ee7eb14116 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 17, 2026, 8:08 p.m.