Triple
T18502676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teen Titans |
E452116
|
entity |
| Predicate | creators |
P7732
|
FINISHED |
| Object | Bob Haney |
—
|
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: Bob Haney | Statement: [Teen Titans, creators, Bob Haney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Haney Context triple: [Teen Titans, creators, Bob Haney]
-
A.
Bob Haney
chosen
Bob Haney was an American comic book writer best known for his influential work at DC Comics, including co-creating the Teen Titans and contributing extensively to Aquaman stories.
-
B.
Bob Hines
Bob Hines was an American wildlife artist and illustrator renowned for his detailed depictions of nature in scientific and environmental publications.
-
C.
Ted Daughety
Ted Daughety is an American physician and pulmonologist best known as the husband of Kansas Governor Laura Kelly.
-
D.
Bill Wittliff
Bill Wittliff was an American screenwriter, author, and photographer best known for adapting and writing acclaimed Western-themed films and television miniseries.
-
E.
Lew Hahn
Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c6384c819091f061c8538f6ca1 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.