Triple
T9738891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain America: The Winter Soldier |
E236134
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Falcon |
E202138
|
NE 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: Falcon | Statement: [Captain America: The Winter Soldier, featuresCharacter, Falcon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Falcon Context triple: [Captain America: The Winter Soldier, featuresCharacter, Falcon]
-
A.
Falcon
The Falcon is a bird of prey known for its exceptional speed, keen vision, and use in the sport of falconry.
-
B.
Falcon
chosen
Falcon is a Marvel Comics superhero and member of the Avengers, known for his advanced winged flight suit and partnership with Captain America.
-
C.
Falcon
Falcon is a family of large language models designed for high-performance text generation and widely used in open-source AI applications.
-
D.
Fighting Falcon
Fighting Falcon is the nickname of the F-16, a widely used American multirole fighter aircraft known for its agility and versatility in combat.
-
E.
Taita falcon
The Taita falcon is a small, rare African bird of prey known for its fast, agile flight and preference for nesting on cliffs in rugged, remote landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ef43fec8190987628f401a27436 |
completed | April 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afe0dab48190832ab77265c09d70 |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:22 p.m.