Triple
T18270999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamela Mann |
E437613
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | David Mann |
—
|
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: David Mann | Statement: [Tamela Mann, spouse, David Mann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Mann Context triple: [Tamela Mann, spouse, David Mann]
-
A.
David Mann
chosen
David Mann is an American actor and comedian best known for his recurring roles in Tyler Perry’s stage plays and films, particularly as the character Mr. Brown.
-
B.
David Mann
David Mann is the harried, everyman motorist relentlessly terrorized by a mysterious truck driver in Steven Spielberg’s thriller film "Duel."
-
C.
David Mann
David Mann is an artist best known for his detailed and dramatic illustrations, particularly in the realms of book and magazine cover art.
-
D.
Robert Mann
Robert Mann was a 19th-century American man best known as the son of influential education reformer Horace Mann.
-
E.
Milton Berlinger
Milton Berlinger, better known by his stage name Milton Berle, was a pioneering American comedian and actor who became one of television’s first major stars.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7e00548190a28916a696831336 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.