Triple
T20664468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Climbing Up Iknimaya – The Path to Heaven |
E507847
|
entity |
| Predicate | filmScene |
P107448
|
FINISHED |
| Object | characters’ climb up Iknimaya |
—
|
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: characters’ climb up Iknimaya | Statement: [Climbing Up Iknimaya – The Path to Heaven, filmScene, characters’ climb up Iknimaya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmScene Context triple: [Climbing Up Iknimaya – The Path to Heaven, filmScene, characters’ climb up Iknimaya]
-
A.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
B.
scenes
chosen
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
C.
filmicFunction
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
-
D.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
E.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f541bc8190ac7946b91647f2b0 |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.