Triple
T30260444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain America: Brave New World |
E769474
|
entity |
| Predicate | LivTylerPlays |
P169030
|
FINISHED |
| Object | Liv Tyler as Betty Ross |
—
|
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: Liv Tyler as Betty Ross | Statement: [Captain America: Brave New World, LivTylerPlays, Liv Tyler as Betty Ross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LivTylerPlays Context triple: [Captain America: Brave New World, LivTylerPlays, Liv Tyler as Betty Ross]
-
A.
Typer
Indicates that one entity serves as the type or classification for another entity.
-
B.
Libby
Indicates a relationship or action involving Libby, though the specific nature of the relationship is not defined by the predicate name alone.
-
C.
player
Indicates that an entity participates in a game, sport, or activity in the role of a player.
-
D.
MacMeans
Indicates that one entity serves as the meaning, definition, or semantic interpretation of another entity.
-
E.
playerNamed
Indicates that a player entity is identified by a specific name.
- F. None of above. chosen
Provenance (4 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_69f22484a5f48190b678cd607700bc82 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f680a8686081908e2d3244655c84fb |
completed | May 2, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 29, 2026, 7:41 p.m.