Triple
T18251384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titans |
E437098
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Gar Logan |
—
|
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: Gar Logan | Statement: [Titans, mainCharacter, Gar Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gar Logan Context triple: [Titans, mainCharacter, Gar Logan]
-
A.
Bob Logan
Bob Logan is a film director and screenwriter best known for co-directing the animated feature "The Lego Ninjago Movie."
-
B.
Steve Logan
Steve Logan is the central protagonist of Ken Follett’s thriller novel "The Third Twin," around whom the mystery of genetic experimentation and identity unfolds.
-
C.
Mike Logan
Mike Logan is a tough, impulsive New York City detective from the Law & Order franchise known for his streetwise attitude and occasional clashes with authority.
-
D.
Doug Logan
Doug Logan is an American sports executive best known as the inaugural commissioner of Major League Soccer.
-
E.
Mark Logan
chosen
Mark Logan is the human alter ego and adoptive father figure of the DC Comics superhero Beast Boy, also known as Garfield Logan.
- 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.