Triple
T23406562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | What About Joan? |
E559949
|
entity |
| Predicate | unairedEpisodes |
P152141
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [What About Joan?, unairedEpisodes, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unairedEpisodes Context triple: [What About Joan?, unairedEpisodes, 9]
-
A.
hasEpisodes
Indicates that one entity (typically a series or show) contains or is composed of multiple episode entities.
-
B.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
C.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
D.
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.
-
E.
intendedEpisodes
Indicates that one entity is planned or designated to appear in, be used for, or be associated with specific episodes of another entity (such as a series or program).
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50e607c8190ba0a22e89862a2d9 |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:38 p.m.