Triple
T5448884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heaven's Mirror |
E122317
|
entity |
| Predicate | theoryType |
P64372
|
FINISHED |
| Object | alternative history |
—
|
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: alternative history | Statement: [Heaven's Mirror, theoryType, alternative history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoryType Context triple: [Heaven's Mirror, theoryType, alternative history]
-
A.
definitionType
Indicates the specific kind or category of definition that characterizes how one entity is defined in relation to another.
-
B.
termType
Indicates the classification or category of a term within a system, specifying what kind of term it is (e.g., type, role, or function) in relation to others.
-
C.
thesisType
Indicates the specific category or kind of thesis associated with an academic work or degree.
-
D.
typology
Indicates a classification relationship in which entities are grouped or organized according to shared types, patterns, or structural characteristics.
-
E.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd95bd53f48190a03144beb290f2cb |
completed | March 20, 2026, 6:45 p.m. |
Created at: March 20, 2026, 2:07 p.m.