Triple
T9112686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupert Graves as DI Greg Lestrade |
E218639
|
entity |
| Predicate | seriesEpisodeOfFirstAppearance |
P16444
|
FINISHED |
| Object | Episode 1 |
—
|
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: Episode 1 | Statement: [Rupert Graves as DI Greg Lestrade, seriesEpisodeOfFirstAppearance, Episode 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesEpisodeOfFirstAppearance Context triple: [Rupert Graves as DI Greg Lestrade, seriesEpisodeOfFirstAppearance, Episode 1]
-
A.
firstAppearanceEpisodeNumber
Indicates the episode number in which an entity (such as a character or item) first appears.
-
B.
firstAppearanceEpisode
chosen
Indicates the specific episode in which an entity (such as a character or item) is shown or mentioned for the first time.
-
C.
firstEpisode
Indicates that one entity is the initial or earliest episode in the series or sequence associated with another entity.
-
D.
seriesOrderOfFirstAppearance
Indicates the position in which an entity first appears within a series, relative to other entities in that same series.
-
E.
firstMentionedInSeries
Indicates the work, episode, or installment in a series where a given entity is introduced or appears for the first time.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca84b0a048190964f560f78e27cce |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:16 p.m.