Triple
T33818353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galahad (Kingsman codename) |
E866754
|
entity |
| Predicate | firstHolderInFilms |
P206682
|
FINISHED |
| Object | Harry Hart |
E48818
|
NE 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: Harry Hart | Statement: [Galahad (Kingsman codename), firstHolderInFilms, Harry Hart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstHolderInFilms Context triple: [Galahad (Kingsman codename), firstHolderInFilms, Harry Hart]
-
A.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
B.
firstUsedInFeatureFilm
Indicates that something (such as a technique, character, or element) made its earliest appearance or application in a particular feature film.
-
C.
featureFilmDebut
Indicates that a work marks an entity’s first appearance or role in a feature-length film.
-
D.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
-
E.
filmDebutFor
Indicates that a particular work marks the first film appearance or role of a given person.
- F. None of above. chosen
Provenance (5 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_69f349911a8c81908478662194b23d8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3689c04b2c8190b6c4ef7fe6d04669 |
completed | June 20, 2026, 12:38 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:46 a.m.