Triple
T25297119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhallaladeva |
E634243
|
entity |
| Predicate | bodyTypeInFiction |
P158364
|
FINISHED |
| Object | muscular |
—
|
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: muscular | Statement: [Bhallaladeva, bodyTypeInFiction, muscular]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyTypeInFiction Context triple: [Bhallaladeva, bodyTypeInFiction, muscular]
-
A.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
B.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
C.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
D.
bodyTypeDepicted
Indicates that one entity visually represents or portrays the physical body type of another entity.
-
E.
featuresFictionalForm
Indicates that one entity includes, presents, or incorporates a fictional representation or version of another entity.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48fd2e5ec8190965046138f838057 |
completed | May 1, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:22 p.m.