Triple
T2630387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DBX |
E59617
|
entity |
| Predicate | underlyingCompanySubsector |
P14918
|
FINISHED |
| Object | Software |
—
|
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: Software | Statement: [DBX, underlyingCompanySubsector, Software]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underlyingCompanySubsector Context triple: [DBX, underlyingCompanySubsector, Software]
-
A.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
B.
underlyingCompany
Indicates that one entity serves as the fundamental or base company upon which another entity (such as a product, instrument, or structure) is built, derived, or dependent.
-
C.
underlyingCompanyName
Indicates the name of the company that serves as the foundational or primary entity underlying another entity, structure, or instrument.
-
D.
underlyingCompanyBusinessFocus
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
E.
hasGICSSubIndustry
chosen
Indicates that an entity is classified within a specific GICS (Global Industry Classification Standard) sub-industry category.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.