Triple
T5894050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAXI |
E131059
|
entity |
| Predicate | relatedIndex |
P5158
|
FINISHED |
| Object | DAX 40 |
E23523
|
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: DAX 40 | Statement: [GDAXI, relatedIndex, DAX 40]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DAX 40 Context triple: [GDAXI, relatedIndex, DAX 40]
-
A.
DAX
chosen
DAX is Germany’s leading blue-chip stock market index, tracking the performance of major companies listed on the Frankfurt Stock Exchange.
-
B.
DAX
DAX (DynamoDB Accelerator) is a fully managed, in-memory caching service designed to significantly speed up read performance for Amazon DynamoDB applications.
-
C.
DAX
DAX (Data Analysis Expressions) is a formula and query language used in Microsoft Power BI, Excel Power Pivot, and Analysis Services for creating custom calculations and data models.
-
D.
MDAX
MDAX is a German stock market index that tracks the performance of 50 mid-cap companies listed on the Frankfurt Stock Exchange.
-
E.
DAX 50 ESG
DAX 50 ESG is a German stock market index that tracks the performance of 50 large, liquid companies from the DAX universe selected based on environmental, social, and governance (ESG) criteria.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f220dc8190ad553d33de4e2ecd |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b15146888190ab86eaf9e565ee28 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.