Triple
T2187585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Favorite Husband |
E49185
|
entity |
| Predicate | hasEpisodeLength |
P11339
|
FINISHED |
| Object | approximately 30 minutes |
—
|
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: approximately 30 minutes | Statement: [My Favorite Husband, hasEpisodeLength, approximately 30 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpisodeLength Context triple: [My Favorite Husband, hasEpisodeLength, approximately 30 minutes]
-
A.
hasEpisodeLengthType
Indicates the type or category of duration associated with an episode (e.g., standard length, short, extended).
-
B.
hasEpisodeRuntime
chosen
Indicates the duration of time that each individual episode of a series or show runs.
-
C.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
D.
hasEpisodeStructure
Indicates that one entity defines or possesses the episodic organization, sequencing, or structural pattern of another (such as a series, season, or narrative work).
-
E.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf9e99f08190892d34485c8f2f25 |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda32d1881909d1fd83a751fb21c |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.