Triple
T16909704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Vasser |
E410161
|
entity |
| Predicate | appearsOnEpisodeCount |
P45771
|
FINISHED |
| Object | all episodes of Journeyman |
—
|
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: all episodes of Journeyman | Statement: [Dan Vasser, appearsOnEpisodeCount, all episodes of Journeyman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsOnEpisodeCount Context triple: [Dan Vasser, appearsOnEpisodeCount, all episodes of Journeyman]
-
A.
appearedInEpisodeOf
Indicates that one entity made an appearance in a specific episode belonging to a television or radio series associated with the other entity.
-
B.
appearsInEpisodeType
Indicates that an entity is featured in, or associated with, a specific type or category of episode.
-
C.
notableEpisodeCount
chosen
Indicates the number of episodes in which the subject is notably featured or recognized.
-
D.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
E.
appearsInSeriesBy
Indicates that one entity (such as a work or character) is featured within a series that is created, authored, or produced by another entity.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3bdc3081908a9b4f6e63405348 |
completed | April 18, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.