Triple
T9564865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planetary Union |
E230764
|
entity |
| Predicate | hasNotableOfficer |
P59056
|
FINISHED |
| Object | Bortus |
E34009
|
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: Bortus | Statement: [Planetary Union, hasNotableOfficer, Bortus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bortus Context triple: [Planetary Union, hasNotableOfficer, Bortus]
-
A.
Bortus
chosen
Bortus is a stoic, duty-bound Moclan officer serving as second-in-command aboard the exploratory spaceship in the sci-fi comedy series "The Orville."
-
B.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
C.
Borz
Borz is the nickname of Khamzat Chimaev, a dominant Chechen-born mixed martial artist competing in the UFC.
-
D.
Bomer
Bomer is the surname of American actor Matt Bomer, known for his roles in television and film such as "White Collar" and "The Normal Heart."
-
E.
Bartel
Bartel is the given name of Bartel Leendert van der Waerden, a prominent Dutch mathematician known for his work in algebra and number theory.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd996a01b081908e2782f41520f73d |
completed | April 1, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152a56f0481908f36df2d4d1291f2 |
completed | April 4, 2026, 6:04 p.m. |
Created at: March 30, 2026, 8:04 p.m.