Triple
T5894057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAXI |
E131059
|
entity |
| Predicate | belongsToMarketSegment |
P54067
|
FINISHED |
| Object | German blue-chip equities |
—
|
LITERAL 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: German blue-chip equities | Statement: [GDAXI, belongsToMarketSegment, German blue-chip equities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToMarketSegment Context triple: [GDAXI, belongsToMarketSegment, German blue-chip equities]
-
A.
belongsToSegment
chosen
Indicates that an entity is a member of, or associated with, a specific segment or subgroup within a larger set.
-
B.
hasMarketRole
Indicates that an entity holds or performs a specific functional role within a market or marketplace context.
-
C.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
D.
marketSegmentCoverage
Indicates the extent to which a product, service, or campaign reaches or serves the intended market segment(s).
-
E.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
- F. None of above.
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_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:58 p.m.