Triple
T11792964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Acker |
E280432
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Acker |
E935553
|
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: Acker | Statement: [Jean Acker, familyName, Acker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Acker Context triple: [Jean Acker, familyName, Acker]
-
A.
Acker
chosen
Acker is a surname of German origin that is a variant of the name Ackers.
-
B.
Albeck
Albeck is a small village in the German state of Baden-Württemberg, notable as the birthplace of industrialist Robert Bosch.
-
C.
Gottesacker
Gottesacker is a German term meaning “God’s field,” traditionally used to refer to a Christian burial ground or cemetery.
-
D.
Oker
The Oker is a river in central Germany that flows northward from the Harz Mountains through Lower Saxony before joining the Aller.
-
E.
Ackley
Ackley is a socially awkward, unhygienic classmate of Holden Caulfield in J.D. Salinger’s novel "The Catcher in the Rye," often serving as a source of irritation and alienation for the protagonist.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a082d08190a42541396a06ed98 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f09115c66c8190b0a3e775bdf575c1 |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 8, 2026, 9:42 p.m.