Triple
T19860745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Deutch |
E477250
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Deutch |
—
|
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: Deutch | Statement: [Howard Deutch, familyName, Deutch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deutch Context triple: [Howard Deutch, familyName, Deutch]
-
A.
Deutch
chosen
Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
-
B.
Deutsch
Deutsch is a surname of German origin borne by numerous individuals across various fields, including arts, sciences, and public life.
-
C.
Deutsche
Deutsche is a German term meaning "German," commonly used in the names of German institutions, companies, and cultural entities.
-
D.
Alemão
Alemão is a former Brazilian midfielder best known for his influential role at Napoli in the late 1980s and early 1990s, where he helped the club achieve major European and domestic success.
-
E.
German
German is a West Germanic language widely spoken in Central Europe and used as an official language in several countries, including Germany, Austria, Switzerland, and Luxembourg.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589a68b081908c2f333b6a292a1f |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.