Triple
T14053759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rifleman |
E338157
|
entity |
| Predicate | hasEpisodes |
P112643
|
FINISHED |
| Object | multiple standalone stories set in North Fork |
—
|
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: multiple standalone stories set in North Fork | Statement: [The Rifleman, hasEpisodes, multiple standalone stories set in North Fork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpisodes Context triple: [The Rifleman, hasEpisodes, multiple standalone stories set in North Fork]
-
A.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
B.
hasEpisodeCountInFirstSeries
Indicates that an entity has a specific number of episodes in its first series or season.
-
C.
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).
-
D.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
E.
hasEP
Indicates that an entity possesses, is associated with, or is characterized by a specific EP (e.g., an endpoint, event point, or designated EP resource) in the given context.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8bc54c8190a12f0fc056568538 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.