Triple
T22716339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anger Management (TV series) |
E561740
|
entity |
| Predicate | hasEpisodeCountOrder |
P149421
|
FINISHED |
| Object | 10-episode initial order |
—
|
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: 10-episode initial order | Statement: [Anger Management (TV series), hasEpisodeCountOrder, 10-episode initial order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpisodeCountOrder Context triple: [Anger Management (TV series), hasEpisodeCountOrder, 10-episode initial order]
-
A.
hasEpisodeCountPerSeries
Indicates a relationship where a series is associated with the number of episodes it contains.
-
B.
hasEpisodeCountInFirstSeries
Indicates that an entity has a specific number of episodes in its first series or season.
-
C.
hasEpisodeList
Indicates that an entity is associated with a collection or sequence of episodes, typically ordered as a list.
-
D.
hasNumberOfEPs
Indicates the quantity or count of EPs (e.g., episodes, extended plays, or similar units) associated with an entity.
-
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. 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790e14c88190af6acb27910ae9c1 |
completed | April 29, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:19 p.m.