Triple
T29661593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elias & Co. |
E750420
|
entity |
| Predicate | hasSubsections |
P18460
|
FINISHED |
| Object | multiple themed retail rooms |
—
|
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: multiple themed retail rooms | Statement: [Elias & Co., hasSubsections, multiple themed retail rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubsections Context triple: [Elias & Co., hasSubsections, multiple themed retail rooms]
-
A.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
B.
hasChildrenSection
Indicates that an entity includes or is associated with a dedicated section that contains information about its children.
-
C.
containsSubchapter
chosen
Indicates that one chapter or section includes another, more specific subchapter as a part of its structure.
-
D.
hasSubSeries
Indicates that one series is a subordinate or component series within a larger parent series.
-
E.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
- 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_69f0d62418a08190a401b127adf9f8a6 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: April 28, 2026, 6:58 p.m.