Triple
T10738162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primary Colors |
E253248
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Libby Holden |
E460573
|
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: Libby Holden | Statement: [Primary Colors, character, Libby Holden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libby Holden Context triple: [Primary Colors, character, Libby Holden]
-
A.
Alexandra Holden
chosen
Alexandra Holden is an American actress known for her roles in films like "Drop Dead Gorgeous" and appearances on television series such as "Friends" and "Ally McBeal."
-
B.
Libby Holman
Libby Holman was an American torch singer and Broadway actress of the 1920s and 1930s, known for her sultry style, dramatic personal life, and influential interpretations of popular songs.
-
C.
Libby Snyder
Libby Snyder is known as the spouse of American poet James Wright.
-
D.
Libby Leist
Libby Leist is a television news executive best known for her leadership role as an executive producer at NBC’s "Today" show.
-
E.
Libby Geist
Libby Geist is an American documentary film producer best known for her work on acclaimed sports and social-issue documentaries, including the Oscar-winning "O.J.: Made in America."
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710410a04819090036597ac0d271c |
completed | April 9, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c7d11cf081908f714686f582c081 |
completed | April 18, 2026, 6:05 p.m. |
Created at: April 8, 2026, 9:14 p.m.