Triple
T7498408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Pepper |
E177192
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | El Brendel |
E470461
|
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: El Brendel | Statement: [Hot Pepper, starring, El Brendel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Brendel Context triple: [Hot Pepper, starring, El Brendel]
-
A.
El Brendel
chosen
El Brendel was an American vaudeville and film comedian best known for his faux-Swedish accent and comic relief roles in early Hollywood talkies.
-
B.
Hölldobler
Hölldobler is a German surname most notably associated with Bert Hölldobler, a prominent behavioral ecologist and myrmecologist known for his research on ants.
-
C.
Die Bertinis
Die Bertinis is a German television miniseries based on Ralph Giordano’s semi-autobiographical novel about a Jewish-Italian family in Hamburg during the Nazi era.
-
D.
Keutenberg
Keutenberg is a famously steep and decisive hill in the Dutch Limburg region, often shaping the outcome of professional cycling races.
-
E.
Else Bremer
Else Bremer was the wife of German Lutheran pastor and anti-Nazi theologian Martin Niemöller.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f597a0c08190b34fa283a11d98c7 |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c8b28d0819095c7b666d442c7ab |
completed | March 28, 2026, 8:39 p.m. |
Created at: March 27, 2026, 3:44 p.m.