Triple
T8298129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gus Gerard |
E194273
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gus |
E328439
|
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: Gus | Statement: [Gus Gerard, givenName, Gus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gus Context triple: [Gus Gerard, givenName, Gus]
-
A.
Gus
Gus is the lovable, chubby mouse in Disney's 1950 animated film "Cinderella," known for his comic relief and loyal friendship to Cinderella.
-
B.
Gus
chosen
Gus is the given name of American filmmaker Gus Van Sant, known for directing independent and mainstream films such as "Good Will Hunting" and "Milk."
-
C.
Gus
Gus is the nickname of Virgil "Gus" Grissom, one of NASA's original Mercury Seven astronauts and a pioneering American spacefarer.
-
D.
Gus
Gus is a character from T. S. Eliot's "Old Possum's Book of Practical Cats," depicted as an elderly, once-famous theater cat reflecting nostalgically on his past glory.
-
E.
Gus
Gus is a character in the 1951 American drama film "Journey into Light," which follows a troubled minister seeking redemption in Los Angeles.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7dfa040c8190ab801b3910e39142 |
completed | March 31, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc6dc4008819084eff0960917494c |
completed | April 2, 2026, 1:31 a.m. |
Created at: March 30, 2026, 5:53 p.m.