Triple
T32031805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley Keener |
E817982
|
entity |
| Predicate | sceneIn |
P107448
|
FINISHED |
| Object | Avengers: Endgame final funeral scene |
—
|
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: Avengers: Endgame final funeral scene | Statement: [Harley Keener, sceneIn, Avengers: Endgame final funeral scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneIn Context triple: [Harley Keener, sceneIn, Avengers: Endgame final funeral scene]
-
A.
scenes
chosen
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
B.
sceneTitle
Indicates that an entity serves as the title or name assigned to a particular scene.
-
C.
sceneStatus
Indicates the current state or condition of a scene within a given context or process.
-
D.
showsScene
Indicates that one entity (such as a media item or visual representation) depicts or presents a particular scene.
-
E.
sceneLabel
Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
- 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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b4960b948190ab62e0b5f8bd5537 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:18 a.m.