Triple
T18251389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titans |
E437098
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Conner Kent |
—
|
NE NERFINISHED |
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: Conner Kent | Statement: [Titans, mainCharacter, Conner Kent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Conner Kent Context triple: [Titans, mainCharacter, Conner Kent]
-
A.
Conner Kent
chosen
Conner Kent is a DC Comics superhero better known as Superboy, a clone combining Kryptonian and human DNA who serves as a prominent member of the Superman family and various teen hero teams.
-
B.
Conner
Conner is a municipality located in the province of Apayao in the Cordillera Administrative Region of the Philippines.
-
C.
Conner
Conner is the surname of American gymnast and Olympic gold medalist Bart Conner.
-
D.
Grayson Kent
Grayson Kent is a central character in the legal dramedy "Drop Dead Diva," portrayed as a charming and principled attorney who serves as the main love interest of the show's protagonist.
-
E.
Conner Wallace
Conner Wallace is a fictional character portrayed by actor Eddie Cahill, best known as a central figure in the legal drama series "Conviction."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd8124648190ae7fc9f1fc5cf9bd |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:33 a.m.