Triple
T20711507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talent Associates |
E509056
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | He & She |
—
|
NE NERFINISHED |
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: He & She | Statement: [Talent Associates, notableWork, He & She]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: He & She Context triple: [Talent Associates, notableWork, He & She]
-
A.
He & She
chosen
"He & She" is a late-1960s American sitcom starring Jack Cassidy, known for its sophisticated, ahead-of-its-time blend of marital comedy and show-business satire.
-
B.
Him & Her
Him & Her is a British television sitcom that follows the mundane yet humorous lives of a lazy couple in their twenties, known for its naturalistic style and intimate, single-location setting.
-
C.
And She Was
"And She Was" is a 1985 new wave song by Talking Heads, known for its surreal lyrics and upbeat, guitar-driven sound.
-
D.
He Loves and She Loves
"He Loves and She Loves" is a romantic song by George and Ira Gershwin, introduced in the 1927 musical film "Funny Face."
-
E.
She & Him
She & Him is an American musical duo featuring Zooey Deschanel and M. Ward, known for their retro-inspired indie pop and folk sound.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c40ad88190b81f77695366d328 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1cdcaac8190b9ba82d489fb3bfc |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:15 p.m.