Triple
T19454359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Martin Brenner |
E486697
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Papa |
—
|
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: Papa | Statement: [Dr. Martin Brenner, alsoKnownAs, Papa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Papa Context triple: [Dr. Martin Brenner, alsoKnownAs, Papa]
-
A.
Papa
chosen
Papa is the sinister scientist and manipulative father-figure who runs the Hawkins Laboratory and experiments on Eleven and other children in the series "Stranger Things."
-
B.
Papa
Papa is the surname of American stand-up comedian, actor, and radio host Tom Papa.
-
C.
Papa
Papa is one of the main playable characters in the Japanese Famicom platform game Yume Kōjō: Doki Doki Panic, which later served as the basis for Super Mario Bros. 2 in the West.
-
D.
Papa
Papa is a central figure in Anita Desai’s novel "Fasting, Feasting," representing the authoritarian, tradition-bound patriarch whose attitudes shape the family’s constrained domestic life.
-
E.
Papa
"Papa" is a stage play by American playwright Zoe Akins, best known for its exploration of family dynamics and character-driven drama.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c117ac8190a38c01c3191beaea |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.