Triple
T7221965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant Shapps |
E150279
|
entity |
| Predicate | hasAlias |
P455
|
FINISHED |
| Object | Michael Green |
E26834
|
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: Michael Green | Statement: [Grant Shapps, hasAlias, Michael Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Green Context triple: [Grant Shapps, hasAlias, Michael Green]
-
A.
Michael Green
chosen
Michael Green is a prominent British theoretical physicist known for his pioneering work in string theory and quantum gravity.
-
B.
Michael Green
Michael Green is an American screenwriter and producer known for his work on major films and television series, including projects like "Logan," "Blade Runner 2049," and "American Gods."
-
C.
David M. Green
David M. Green is a distinguished figure in the field of acoustics recognized for his significant contributions with the prestigious ASA Gold Medal.
-
D.
Michael V. Drake
Michael V. Drake is an American academic leader and physician who has served as president of both The Ohio State University and the University of California system.
-
E.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9b42c5c81908c405f161c35ffb4 |
completed | March 27, 2026, 8:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc0c3ff08190b855fa57967586ce |
completed | March 28, 2026, 12:39 p.m. |
Created at: March 27, 2026, 2:54 p.m.