Triple
T17856775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Howard |
E445958
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Michael Hecht |
—
|
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: Michael Hecht | Statement: [Michael Howard, birthName, Michael Hecht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Hecht Context triple: [Michael Howard, birthName, Michael Hecht]
-
A.
Michael Hecht
chosen
Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
-
B.
Michael Hecht
Michael Hecht is a scientist best known for leading NASA’s MOXIE experiment on the Perseverance rover, which demonstrates in-situ oxygen production on Mars.
-
C.
Michael Tuchner
Michael Tuchner was a British film and television director known for his work on crime dramas and character-driven stories in the 1960s and 1970s.
-
D.
Michael Jaffe
Michael Jaffe is an American television and film producer known for his work on numerous TV movies, series, and feature films.
-
E.
Michael Hertzberg
Michael Hertzberg is an American film producer best known for his work on several Mel Brooks comedies, including "Blazing Saddles" and "Silent Movie."
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978bd5e081909e192f6aada5235f |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 10:17 a.m.