Triple
T2092019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Facts of Life |
E32690
|
entity |
| Predicate | hasSpecialEpisodeType |
P16447
|
FINISHED |
| Object | very special episode |
—
|
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: very special episode | Statement: [The Facts of Life, hasSpecialEpisodeType, very special episode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialEpisodeType Context triple: [The Facts of Life, hasSpecialEpisodeType, very special episode]
-
A.
includesSpecialEpisodes
chosen
Indicates that the subject collection or series contains one or more special, non-regular episodes.
-
B.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
C.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
-
D.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
E.
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).
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba7626d081908c9c0f18942e128d |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.