Triple
T9447403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminator: Dark Fate |
E227797
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Ken Seng |
E201578
|
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: Ken Seng | Statement: [Terminator: Dark Fate, cinematographyBy, Ken Seng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Seng Context triple: [Terminator: Dark Fate, cinematographyBy, Ken Seng]
-
A.
Ken Seng
chosen
Ken Seng is a cinematographer known for his visually distinctive work on films such as "Obsessed."
-
B.
Chan Sek Keong
Chan Sek Keong is a prominent Singaporean jurist who served as the country’s third Chief Justice and played a key role in shaping its modern legal system.
-
C.
Mark Chee
Mark Chee is a molecular biologist and entrepreneur best known as a co-founder of Illumina, a leading company in DNA sequencing and genomics technologies.
-
D.
Kok Keong
Kok Keong is a given name most notably associated with Foo Kok Keong, a former Malaysian badminton player renowned for his fighting spirit and defensive play.
-
E.
Anthony Tan
Anthony Tan is a Malaysian entrepreneur best known as the co-founder and CEO of Grab, Southeast Asia’s leading super-app for ride-hailing, deliveries, and digital financial services.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f35394c8190aa77528dabd6139c |
completed | April 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1106aeb708190bbbe1d05b7472194 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:51 p.m.