Triple
T10400470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Gries |
E245131
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tom Gries |
E245131
|
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: Tom Gries | Statement: [Tom Gries, name, Tom Gries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Gries Context triple: [Tom Gries, name, Tom Gries]
-
A.
Tom Gries
chosen
Tom Gries was an American film and television director, producer, and screenwriter known for his work on action and Western projects in the 1960s and 1970s.
-
B.
Ray Heindorf
Ray Heindorf was an American composer, arranger, and musical director best known for his work on numerous Hollywood film scores during the mid-20th century.
-
C.
Tom Gola
Tom Gola was an American Hall of Fame basketball player and coach renowned for his collegiate stardom at La Salle University and successful NBA career, primarily with the Philadelphia Warriors.
-
D.
Tom Schaul
Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
-
E.
Greg Hirsch
Greg Hirsch is a bumbling yet opportunistic young relative of the Roy family in the television series "Succession," known for his awkward social skills and surprising knack for survival in the corporate power struggle.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e2f11c8190b30695cba2975544 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbd13c888190b3a79a9aacb5291e |
completed | April 9, 2026, 7:19 p.m. |
Created at: April 6, 2026, 12:07 p.m.