Triple
T11859686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legally Blonde (Broadway musical) |
E282128
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Nell Benjamin |
E387451
|
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: Nell Benjamin | Statement: [Legally Blonde (Broadway musical), composer, Nell Benjamin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nell Benjamin Context triple: [Legally Blonde (Broadway musical), composer, Nell Benjamin]
-
A.
Nell Benjamin
chosen
Nell Benjamin is an American lyricist and composer best known for her work on Broadway musicals such as Legally Blonde and Mean Girls.
-
B.
Nancy Dowd
Nancy Dowd is an American screenwriter best known for her Oscar-winning work on the anti-war film "Coming Home" and for writing the cult hockey movie "Slap Shot."
-
C.
Jill Krementz
Jill Krementz is an American photographer and author best known for her portraits of writers and her work in children's literature.
-
D.
Rachel Singer
Rachel Singer is a former Mossad agent whose past mission to capture a Nazi war criminal haunts her decades later in the thriller film "The Debt."
-
E.
Gail Berke
Gail Berke is a central protagonist in the adventure film "The Deep," known for becoming entangled in a dangerous underwater treasure hunt.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69a099c8190a674db64c50eca5a |
completed | April 10, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f417a954e881909fdd9626d41229e2 |
completed | May 1, 2026, 3:02 a.m. |
Created at: April 8, 2026, 9:43 p.m.