Triple
T16098490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Feeney |
E390548
|
entity |
| Predicate | featuredInEpisodeCountApprox |
P45771
|
FINISHED |
| Object | 178 |
—
|
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: 178 | Statement: [Shirley Feeney, featuredInEpisodeCountApprox, 178]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInEpisodeCountApprox Context triple: [Shirley Feeney, featuredInEpisodeCountApprox, 178]
-
A.
notableEpisodeCount
chosen
Indicates the number of episodes in which the subject is notably featured or recognized.
-
B.
appearedInEpisodeOf
Indicates that one entity made an appearance in a specific episode belonging to a television or radio series associated with the other entity.
-
C.
notableEP
Indicates that an entity is especially well-known or significant for a particular EP (extended play recording).
-
D.
appearsInEpisodeType
Indicates that an entity is featured in, or associated with, a specific type or category of episode.
-
E.
hasEpisodeAbout
Indicates that a particular episode (such as of a show, podcast, or series) focuses on, discusses, or is centered around a specified subject or topic.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6551a48190afb7e0c61e22b541 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:59 a.m.