Triple
T36505451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark troopers |
E899447
|
entity |
| Predicate | firstCanonAppearanceSeason |
P115402
|
FINISHED |
| Object | Season 2 |
—
|
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: Season 2 | Statement: [Dark troopers, firstCanonAppearanceSeason, Season 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCanonAppearanceSeason Context triple: [Dark troopers, firstCanonAppearanceSeason, Season 2]
-
A.
firstAppearanceEpisode
Indicates the specific episode in which an entity (such as a character or item) is shown or mentioned for the first time.
-
B.
firstUsedInSeason
chosen
Indicates the season in which something (such as a character, item, or concept) was first introduced or used.
-
C.
firstAppearanceEpisodeNumber
Indicates the episode number in which an entity (such as a character or item) first appears.
-
D.
firstAppearanceFranchise
Indicates the franchise in which an entity made its first appearance.
-
E.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
- 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.