Triple
T37168719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Chidlom |
E920854
|
entity |
| Predicate | hasElectronicsSection |
P139029
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Central Chidlom, hasElectronicsSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectronicsSection Context triple: [Central Chidlom, hasElectronicsSection, yes]
-
A.
hasElectronicsFeature
Indicates that an entity possesses or is characterized by a specific electronic-related feature or capability.
-
B.
hasOnlineShop
Indicates that an entity operates or is associated with a shop that sells goods or services via the internet.
-
C.
isElectronicOnly
Indicates that the item or resource exists solely in digital form and is not available in any physical format.
-
D.
shopSection
chosen
Indicates the specific section or area within a shop where an item, activity, or service is located or takes place.
-
E.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: May 3, 2026, 4:15 p.m.