Triple
T31571849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lone Star |
E805585
|
entity |
| Predicate | numberOfProducedEpisodes |
P2593
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Lone Star, numberOfProducedEpisodes, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfProducedEpisodes Context triple: [Lone Star, numberOfProducedEpisodes, 5]
-
A.
numberOfEpisodes
chosen
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
originallyPlannedNumberOfEpisodes
Indicates the total number of episodes that were initially intended or planned for a series or program before any changes occurred.
-
C.
hasEpisodeCountInFirstSeries
Indicates that an entity has a specific number of episodes in its first series or season.
-
D.
hasEpisodes
Indicates that one entity (typically a series or show) contains or is composed of multiple episode entities.
-
E.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
- 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_69f348d2ee94819091918d1789398c29 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0123d1162c81908182d01ba3ddd236 |
completed | May 11, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_6a01236713d88190b12a567c0dfb2d49 |
completed | May 11, 2026, 12:31 a.m. |
Created at: April 30, 2026, 10:20 p.m.