Triple
T22122297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herb Alpert |
E546700
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Lani Hall |
—
|
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: Lani Hall | Statement: [Herb Alpert, spouse, Lani Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lani Hall Context triple: [Herb Alpert, spouse, Lani Hall]
-
A.
Lani Hall
chosen
Lani Hall is an American singer best known as the original lead vocalist of Sergio Mendes & Brasil '66 and for her later solo work and collaborations with her husband, Herb Alpert.
-
B.
Lani Weymouth
Lani Weymouth is a musician best known as a member of the new wave band Tom Tom Club, formed by Talking Heads members Chris Frantz and Tina Weymouth.
-
C.
Lani O'Grady
Lani O'Grady was an American actress best known for her role as Mary Bradford on the television series "Eight Is Enough."
-
D.
Donna Dixon
Donna Dixon is an American actress and former model known for her roles in 1980s comedies and for her long career in film and television.
-
E.
Arlene Lorenzo
Arlene Lorenzo is a fictional character who serves as the primary protagonist in the story featuring Dick.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1297f3fb48190b6aaca18b40c37ab |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:31 p.m.