Triple
T36491747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omniglot |
E899066
|
entity |
| Predicate | eachCharacterHas |
P80161
|
FINISHED |
| Object | 20 instances |
—
|
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: 20 instances | Statement: [Omniglot, eachCharacterHas, 20 instances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eachCharacterHas Context triple: [Omniglot, eachCharacterHas, 20 instances]
-
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.
allyOfCharacter
Indicates that one character maintains an alliance or supportive partnership with another character.
-
D.
eachMemberHas
chosen
Indicates that every individual element within a group or collection possesses or is associated with a specified property, attribute, or item.
-
E.
hasRecurringCharacterFrom
Indicates that one work or series includes a character who also appears recurrently in another work or series.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:10 p.m.