Triple
T32189643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluebell medical clinic |
E822201
|
entity |
| Predicate | appearsInEpisodeCountType |
P193136
|
FINISHED |
| Object | multiple episodes of Hart of Dixie |
—
|
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: multiple episodes of Hart of Dixie | Statement: [Bluebell medical clinic, appearsInEpisodeCountType, multiple episodes of Hart of Dixie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInEpisodeCountType Context triple: [Bluebell medical clinic, appearsInEpisodeCountType, multiple episodes of Hart of Dixie]
-
A.
appearsInEpisodeType
Indicates that an entity is featured in, or associated with, a specific type or category of episode.
-
B.
hasEpisodeCountPerCharacter
Indicates the number of episodes associated with or featuring each individual character.
-
C.
appearedInEpisodeOf
Indicates that one entity made an appearance in a specific episode belonging to a television or radio series associated with the other entity.
-
D.
notableEpisodeCount
Indicates the number of episodes in which the subject is notably featured or recognized.
-
E.
hasEpisodeCountPerSeries
Indicates a relationship where a series is associated with the number of episodes it contains.
- F. None of above. chosen
Provenance (4 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
| PDg | Predicate description generation | batch_69fd389b653c81908a97ab2eff98c6ea |
completed | May 8, 2026, 1:12 a.m. |
Created at: May 1, 2026, 12:35 a.m.