Triple
T23062663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Report |
E574944
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Greg O’Bryant |
—
|
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: Greg O’Bryant | Statement: [The Report, editedBy, Greg O’Bryant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg O’Bryant Context triple: [The Report, editedBy, Greg O’Bryant]
-
A.
Greg O'Bryant
chosen
Greg O'Bryant is a film editor known for his work on independent and character-driven movies, including the 2017 film "Lucky."
-
B.
Brook Lopez
Brook Lopez is an American professional basketball center in the NBA, known for his scoring ability, rim protection, and later-career development into a reliable three-point shooter.
-
C.
Tyus Edney
Tyus Edney is an American former professional basketball player and NCAA champion point guard best known for his clutch play at UCLA and a successful European career.
-
D.
Andray Blatche
Andray Blatche is a Filipino-American former professional basketball player and ex-NBA forward/center who became a prominent import star in the Chinese Basketball Association.
-
E.
Deron Bennett
Deron Bennett is a professional comic book letterer known for his work on various titles across major publishers.
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f189a0c3c881909f137ad511c216ac |
completed | April 29, 2026, 4:31 a.m. |
Created at: April 17, 2026, 3:55 p.m.