Triple
T111431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mako Mori |
E2255
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Travis Beacham |
E30318
|
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: Travis Beacham | Statement: [Mako Mori, creator, Travis Beacham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Travis Beacham Context triple: [Mako Mori, creator, Travis Beacham]
-
A.
Travis Beacham
chosen
Travis Beacham is an American screenwriter best known for co-writing the science fiction monster film "Pacific Rim."
-
B.
Brian VanDeMark
Brian VanDeMark is an American historian and author known for his work on U.S. foreign policy and the Vietnam War, including coauthoring influential studies of that conflict.
-
C.
Cale Boyter
Cale Boyter is a film producer known for his work on major genre and franchise movies, including the science fiction action sequel "Pacific Rim: Uprising."
-
D.
Tony James
Tony James is an American financier and executive best known as the longtime president and chief operating officer of Blackstone and for his leadership roles at major cultural institutions.
-
E.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a256ec650c8190bee2067e37065527 |
completed | Feb. 28, 2026, 2:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a399a12344819097028715c166ecb7 |
completed | March 1, 2026, 1:42 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.