Triple
T20869703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lego House |
E513856
|
entity |
| Predicate | mainCharacterInMusicVideo |
P27644
|
FINISHED |
| Object | obsessive fan portrayed by Rupert Grint |
—
|
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: obsessive fan portrayed by Rupert Grint | Statement: [Lego House, mainCharacterInMusicVideo, obsessive fan portrayed by Rupert Grint]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterInMusicVideo Context triple: [Lego House, mainCharacterInMusicVideo, obsessive fan portrayed by Rupert Grint]
-
A.
musicVideoCameo
Indicates that one entity makes a brief or special-appearance role in the other entity’s music video.
-
B.
hasMusicVideoCharacteristic
Indicates that a music video possesses a specific attribute, feature, or quality.
-
C.
hasMusicVideoPerformer
Indicates that a music video features a specific performer appearing or performing in it.
-
D.
musicalCharacter
chosen
Indicates that one entity is a character or role that appears within the other entity, which is a musical work or production.
-
E.
usesMusicVideo
Indicates that one entity incorporates or features another entity as a music video.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c4637ec48190830023d20fb8124c |
completed | April 21, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a593f481908beb457c29f1ce73 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.