Triple
T35696393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Delhi district |
E1031450
|
entity |
| Predicate | containsCommercialArea |
P202889
|
FINISHED |
| Object | Laxmi Nagar commercial hub |
—
|
NE NERFINISHED |
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: Laxmi Nagar commercial hub | Statement: [East Delhi district, containsCommercialArea, Laxmi Nagar commercial hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCommercialArea Context triple: [East Delhi district, containsCommercialArea, Laxmi Nagar commercial hub]
-
A.
connectsToCommercialArea
Indicates that one location has a direct link, route, or access path to a commercial area.
-
B.
isPrimaryCommercialAreaOf
Indicates that one area serves as the main center of commercial activity for another specified place or region.
-
C.
hasNoCommercialZone
Indicates that the subject area or entity does not contain any designated commercial zone or commercial-use area.
-
D.
hasLimitedCommercialAreas
Indicates that the subject possesses or is characterized by commercial zones that are restricted in size, extent, or availability.
-
E.
hasCommercialCenterType
Indicates that an entity has or is associated with a specific type or category of commercial center (e.g., mall, shopping district, business park).
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00cbae75988190974f5b45a2e62326 |
completed | May 10, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_6a00cabe4c5881909cca5efbe494e0d1 |
completed | May 10, 2026, 6:13 p.m. |
| PDg | Predicate description generation | batch_6a00cbad83e88190ba792d3172370f63 |
completed | May 10, 2026, 6:17 p.m. |
Created at: May 3, 2026, 4:05 p.m.