Triple
T27872225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amilyn Holdo |
E704818
|
entity |
| Predicate | firstAppearanceInCanon |
P29367
|
FINISHED |
| Object | Leia, Princess of Alderaan (novel) |
—
|
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: Leia, Princess of Alderaan (novel) | Statement: [Amilyn Holdo, firstAppearanceInCanon, Leia, Princess of Alderaan (novel)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceInCanon Context triple: [Amilyn Holdo, firstAppearanceInCanon, Leia, Princess of Alderaan (novel)]
-
A.
firstAppearanceFranchise
Indicates the franchise in which an entity made its first appearance.
-
B.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
C.
firstAppearanceFor
chosen
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
D.
firstAppearanceInComicsIssue
Indicates the specific comic book issue in which an entity (such as a character or item) is depicted for the first time.
-
E.
firstPopularAppearance
Indicates the earliest notable or widely recognized appearance of an entity in a public or popular context.
- 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_69ef84111bb4819084298f994b31c62f |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff6a4ce9a08190b98abde3a170dd69 |
completed | May 9, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69ff69c11634819089d1084bd2c11534 |
completed | May 9, 2026, 5:07 p.m. |
Created at: April 27, 2026, 6:25 p.m.