Triple
T10772010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Broadway |
E254101
|
entity |
| Predicate | commercialType |
P72821
|
FINISHED |
| Object | retail |
—
|
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: retail | Statement: [East Broadway, commercialType, retail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commercialType Context triple: [East Broadway, commercialType, retail]
-
A.
commercialCategory
chosen
Indicates the type of commercial classification or business category under which an entity or transaction is grouped.
-
B.
commercialService
Indicates a relationship where one entity provides a paid, profit-oriented service to another entity.
-
C.
commercial
Indicates that one entity is engaged in a business-related or profit-oriented relationship, activity, or transaction with another entity.
-
D.
commercialCustomer
Indicates a relationship where an entity purchases or uses goods or services from another entity for commercial or business purposes.
-
E.
commercialAccess
Indicates that an entity is permitted to use or access something for commercial or profit-generating purposes.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7329a281081909cdc4b971cf69207 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.