Triple
T15363026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SHLD |
E367336
|
entity |
| Predicate | underlyingCompanyPrimaryBusinessArea |
P6749
|
FINISHED |
| Object | United States retail operations |
—
|
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: United States retail operations | Statement: [SHLD, underlyingCompanyPrimaryBusinessArea, United States retail operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underlyingCompanyPrimaryBusinessArea Context triple: [SHLD, underlyingCompanyPrimaryBusinessArea, United States retail operations]
-
A.
primaryBusinessArea
Indicates the main field, sector, or domain in which an entity primarily conducts its business activities.
-
B.
underlyingCompanyBusinessFocus
chosen
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
C.
underlyingCompanyPrimaryMarkets
Indicates the main geographic or sector markets in which the underlying company primarily operates or focuses its business activities.
-
D.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
E.
underlyingCompanyType
Indicates the classification or category of company that forms the basis or source for another related entity or instrument.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e479f188190bbbc3dcd73853e02 |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.