Triple
T25986856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hologram Janeway |
E646225
|
entity |
| Predicate | modeledAfterCharacter |
P117924
|
FINISHED |
| Object | Captain Kathryn Janeway |
—
|
NE NERFINISHED |
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: Captain Kathryn Janeway | Statement: [Hologram Janeway, modeledAfterCharacter, Captain Kathryn Janeway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeledAfterCharacter Context triple: [Hologram Janeway, modeledAfterCharacter, Captain Kathryn Janeway]
-
A.
isModelledAfter
Indicates that one entity is created, designed, or structured based on the form, features, or principles of another entity.
-
B.
nicknameModelledOn
Indicates that one entity’s nickname is based on, inspired by, or patterned after another entity.
-
C.
inspiredByFictionalCharacter
chosen
Indicates that an entity’s characteristics, actions, or creation are influenced or modeled after a specific fictional character.
-
D.
namedAfterFictionalCharacter
Indicates that one entity has been given its name in honor of, or derived from, a fictional character.
-
E.
modeledBy
Indicates that one entity serves as a model or representation of another, typically capturing its structure, behavior, or properties.
- 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_69e77e881fc08190ba1c8dc7e2a07f97 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605446ca48190907baef523f13ccf |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 22, 2026, 8:55 a.m.