Triple
T16380319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Catton |
E397787
|
entity |
| Predicate | closeColleague |
P11349
|
FINISHED |
| Object | Turk Malloy |
E385764
|
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: Turk Malloy | Statement: [Frank Catton, closeColleague, Turk Malloy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turk Malloy Context triple: [Frank Catton, closeColleague, Turk Malloy]
-
A.
Turk Malloy
chosen
Turk Malloy is a skilled driver and member of Danny Ocean’s crew in the "Ocean's" heist film series.
-
B.
Buddy Sorrell
Buddy Sorrell is a wisecracking comedy writer and supporting character on the classic American sitcom "The Dick Van Dyke Show."
-
C.
Andrew Taggart
Andrew Taggart is an American DJ, producer, and songwriter best known as one half of the electronic music duo The Chainsmokers.
-
D.
Andrew Taggart
Andrew Taggart is a contemporary writer and practical philosopher known for his work on the ethics of technology, work, and modern life.
-
E.
Mike Banning
Mike Banning is the fictional Secret Service agent protagonist of the "Has Fallen" action film series, known for protecting the U.S. president in high-stakes terrorist attacks.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319db5b648190a8fca23518a1fb39 |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0035689ef08190ba980a359498ca56 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.