Triple
T20554002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Market, Lajpat Nagar |
E504668
|
entity |
| Predicate | hasShopsOfType |
P140534
|
FINISHED |
| Object | street stalls |
—
|
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: street stalls | Statement: [Central Market, Lajpat Nagar, hasShopsOfType, street stalls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShopsOfType Context triple: [Central Market, Lajpat Nagar, hasShopsOfType, street stalls]
-
A.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
-
B.
hasShop
Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
-
C.
hasIndependentShops
Indicates that an entity contains or is associated with retail businesses that operate independently rather than as part of large chains or franchises.
-
D.
hasCulturalShops
Indicates that a place or area contains shops or stores that sell goods or services associated with specific cultures or cultural traditions.
-
E.
hasConfectioneryShops
Indicates that an entity operates, contains, or is associated with one or more confectionery shops.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5dbe96c8190a278dfefdb4a5c43 |
completed | April 20, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:38 a.m.