Triple
T17090221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menards |
E414702
|
entity |
| Predicate | hasRetailSegment |
P125845
|
FINISHED |
| Object | do-it-yourself customers |
—
|
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: do-it-yourself customers | Statement: [Menards, hasRetailSegment, do-it-yourself customers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailSegment Context triple: [Menards, hasRetailSegment, do-it-yourself customers]
-
A.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
-
B.
hasRetailNetwork
Indicates that an entity operates or is associated with a system of retail outlets or distribution channels through which products or services are sold.
-
C.
hasRetailFormat
Indicates that one entity operates or is organized according to a particular retail format or store type.
-
D.
hasRetailCharacteristic
Indicates that an entity possesses a specific attribute, feature, or quality relevant to retail contexts (such as pricing, packaging, or point-of-sale properties).
-
E.
hasRetailProduct
Indicates that an entity offers, sells, or makes available a particular product in a retail context.
- F. None of above. chosen
Provenance (4 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbf948d88190a4dd4a0774a8505b |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.