Triple
T14191664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hercules (2014 film) |
E351726
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Ryan J. Condal |
E796024
|
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: Ryan J. Condal | Statement: [Hercules (2014 film), screenwriter, Ryan J. Condal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan J. Condal Context triple: [Hercules (2014 film), screenwriter, Ryan J. Condal]
-
A.
Ryan J. Condal
chosen
Ryan J. Condal is an American screenwriter and producer best known for creating the TV series "Colony" and co-creating HBO's "House of the Dragon."
-
B.
Ryan Condal
Ryan Condal is an American screenwriter and producer best known for co-creating and showrunning the Game of Thrones prequel series "House of the Dragon."
-
C.
Kyle Conder
Kyle Conder is a collegiate sports administrator who serves as the athletic director for California State University, Bakersfield’s Roadrunners athletic program.
-
D.
Brian Pimental
Brian Pimental is an American animator, storyboard artist, and director known for his work on several major Disney animated films, including contributing to the story of Beauty and the Beast.
-
E.
Aidan N. Gomez
Aidan N. Gomez is a computer scientist and co-author of the seminal "Attention Is All You Need" paper that introduced the Transformer architecture in deep learning.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61df628c8190ba3f557e2128dce5 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd1946eb68819096adf3c16a39818d |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:04 a.m.