Triple
T5072550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flight of the Hippogriff |
E114313
|
entity |
| Predicate | hasTrainTheme |
P37147
|
FINISHED |
| Object | Hippogriff-shaped cars |
—
|
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: Hippogriff-shaped cars | Statement: [Flight of the Hippogriff, hasTrainTheme, Hippogriff-shaped cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainTheme Context triple: [Flight of the Hippogriff, hasTrainTheme, Hippogriff-shaped cars]
-
A.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
B.
portraysTrainAs
Indicates that one entity represents or depicts a train in a particular way or role.
-
C.
hasThemePark
Indicates that one entity owns, contains, or is associated with a theme park as part of its properties or offerings.
-
D.
hasRackRailway
Indicates that one entity possesses or includes a rack railway system connecting locations or operating within its area.
-
E.
hasAttractionTheme
chosen
Indicates that something (such as a place, event, or attraction) is characterized by or associated with a particular theme or motif.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74cfa4348190bc50590117a6bcf9 |
completed | March 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:39 p.m.