Triple
T17117274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adriana Balboa |
E415371
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Rocky franchise |
E13871
|
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: Rocky franchise | Statement: [Adriana Balboa, partOf, Rocky franchise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rocky franchise Context triple: [Adriana Balboa, partOf, Rocky franchise]
-
A.
Rocky film series
chosen
The Rocky film series is a popular American sports drama franchise centered on underdog boxer Rocky Balboa’s personal and professional struggles and triumphs.
-
B.
Rocky
Rocky is a classic 1976 American sports drama film starring Sylvester Stallone as an underdog boxer who gets an unlikely shot at the world heavyweight title.
-
C.
Rocky
Rocky is a charismatic, adventurous rooster who serves as one of the central protagonists in the animated Chicken Run film series.
-
D.
Rocky
Rocky is the given name of American football coach Rocky Long, known for his long career leading various college teams.
-
E.
Rocky
Rocky is a character who is trained and guided by the wise martial arts master Grandpa Mori Tanaka.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8075a6c8190954d36eb94d1028a |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014145f7988190803d5c5e4f2705b0 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:35 a.m.