Triple
T11050454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruby Serkis |
E261231
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ruby |
E490326
|
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: Ruby | Statement: [Ruby Serkis, givenName, Ruby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruby Context triple: [Ruby Serkis, givenName, Ruby]
-
A.
Ruby
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
-
B.
Ruby
Ruby is a character from the children's animated television series "Dot.," which follows a young tech-savvy girl and her friends as they explore the world using technology and curiosity.
-
C.
Ruby
Ruby is a translucent deep-red color used as one of the signature case options for Apple’s original iMac G3 computers.
-
D.
Ruby
chosen
Ruby is a feminine given name derived from the precious red gemstone, often associated with vitality, love, and elegance.
-
E.
Ruby
Ruby is a character in John Grisham’s legal thriller "The Street Lawyer," playing a role in the novel’s exploration of homelessness, justice, and moral responsibility.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79868c78881908c8e3672c05ae7ec |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3aa146b148190a87205e542cc718f |
completed | April 18, 2026, 3:58 p.m. |
Created at: April 8, 2026, 9:26 p.m.