Triple
T11947320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodyguard |
E284333
|
entity |
| Predicate | hasEpisodeCountInFirstSeries |
P102411
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Bodyguard, hasEpisodeCountInFirstSeries, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpisodeCountInFirstSeries Context triple: [Bodyguard, hasEpisodeCountInFirstSeries, 6]
-
A.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
C.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
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.
numberOfSeriesPerSeason
Indicates the total count of series (or episodes/instalments) that occur within a single season of something.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.