Triple
T5316644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrich Diez |
E119166
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Diez |
E415049
|
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: Diez | Statement: [Friedrich Diez, familyName, Diez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diez Context triple: [Friedrich Diez, familyName, Diez]
-
A.
Diez
chosen
Diez is a small historic town in western Germany’s Rhineland-Palatinate, known for its picturesque setting on the Lahn River and its prominent hilltop castle.
-
B.
Toma
Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
-
C.
Consuela
Consuela is a recurring character on the animated TV series "Family Guy," known as a stubborn, heavily accented Latina maid who often says "No, no, no."
-
D.
Anzures
Anzures is an upscale residential and commercial neighborhood in Mexico City known for its central location, embassies, and proximity to major business and cultural districts.
-
E.
Dieze
The Dieze is a river in the southern Netherlands that flows through the city of ’s-Hertogenbosch and ultimately drains into the Dommel and Aa river system.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd854fd07c8190b4f1c3c8e618c308 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf110e89548190a5eb0bad6ab0483b |
completed | March 21, 2026, 9:43 p.m. |
Created at: March 20, 2026, 1:54 p.m.