Triple
T4114620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armin Mueller-Stahl |
E90261
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mueller-Stahl |
E330529
|
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: Mueller-Stahl | Statement: [Armin Mueller-Stahl, familyName, Mueller-Stahl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mueller-Stahl Context triple: [Armin Mueller-Stahl, familyName, Mueller-Stahl]
-
A.
Müller
Müller is a common German surname, equivalent to "Miller" in English, historically associated with the occupation of operating a mill.
-
B.
Munnier
Munnier was an architect best known for designing Bangkok’s Democracy Monument, a prominent political and historical landmark in Thailand.
-
C.
Millner
Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
-
D.
Meltzer
Meltzer is a surname of Germanic origin borne by various notable individuals across fields such as politics, academia, and the arts.
-
E.
Stahl
chosen
Stahl is a surname of German origin borne by various notable individuals across fields such as sports, politics, and the arts.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01f07c688190a6e3689667587247 |
completed | March 9, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b8e30448190a1ac0df969c83631 |
completed | March 14, 2026, 2:07 p.m. |
Created at: March 9, 2026, 3:41 p.m.