Triple
T6186219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johannes Kleiman |
E138066
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Opekta |
E296565
|
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: Opekta | Statement: [Johannes Kleiman, employer, Opekta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Opekta Context triple: [Johannes Kleiman, employer, Opekta]
-
A.
Opekta
chosen
Opekta was a German-Dutch company that produced and sold pectin-based gelling agents for making jam, notably managed in its Amsterdam branch by Anne Frank’s father, Otto Frank.
-
B.
Plaxtol
Plaxtol is a small rural village and civil parish in Kent, England, known for its historic buildings and surrounding countryside.
-
C.
Auscitain
An Auscitain is a resident or native of Auch, a historic town in the Occitanie region of southwestern France.
-
D.
Optax
Optax is a gradient processing and optimization library for JAX, providing a flexible collection of composable optimizers and transformations for training machine learning models.
-
E.
Singulair
Singulair is a prescription leukotriene receptor antagonist (montelukast) commonly used to prevent and manage asthma and allergy symptoms.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0621671988190938dd16242a2e4d5 |
completed | March 22, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c141ca916c8190bd1ca46f2b8c9c18 |
completed | March 23, 2026, 1:36 p.m. |
Created at: March 22, 2026, 4:19 p.m.