Triple
T37003400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stories of the Gods and Heroes |
E915416
|
entity |
| Predicate | includesCharactersType |
P180826
|
FINISHED |
| Object | gods |
—
|
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: gods | Statement: [Stories of the Gods and Heroes, includesCharactersType, gods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCharactersType Context triple: [Stories of the Gods and Heroes, includesCharactersType, gods]
-
A.
employsCharacterType
chosen
Indicates that an entity makes use of or features a particular type or category of character in its content or structure.
-
B.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
C.
controlledCharacterType
Indicates that one entity specifies or constrains the type or category of character that another entity is allowed to control.
-
D.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
E.
helpsCharacterType
Indicates that one character type provides assistance or support to another character type.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.