Triple
T9417140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Eller |
E227054
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Eller |
E710693
|
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: Eller | Statement: [Carl Eller, familyName, Eller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eller Context triple: [Carl Eller, familyName, Eller]
-
A.
Eller
chosen
Eller is a surname of German origin borne by various notable individuals across different fields.
-
B.
Elers
Elers is a surname of likely European origin associated with individuals such as Anna Maria Elers.
-
C.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
D.
Erikli
Erikli is a Turkish bottled water brand known for its natural spring water, marketed under the Nestlé Waters portfolio.
-
E.
Eilif
Eilif is one of Mother Courage’s sons in Bertolt Brecht’s play "Mother Courage and Her Children," whose experiences as a soldier highlight the brutalizing effects of war.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cb4be08190a47f901a9703f9db |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107bfd73481908e07d0ee2774bd59 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:48 p.m.