Triple
T15065509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyber City, Gurugram |
E379744
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | DLF Cyber Park |
E1134623
|
NE 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: DLF Cyber Park | Statement: [Cyber City, Gurugram, hasLandmark, DLF Cyber Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DLF Cyber Park Context triple: [Cyber City, Gurugram, hasLandmark, DLF Cyber Park]
-
A.
DLF Cyber Hub
DLF Cyber Hub is a popular corporate, dining, and entertainment complex in Gurugram, India, known for its upscale restaurants, bars, and vibrant nightlife.
-
B.
DLF Cyber Greens
chosen
DLF Cyber Greens is a prominent commercial office complex in Gurugram’s Cyber City business district, housing numerous multinational corporations and technology companies.
-
C.
Cybercity Magarpatta
Cybercity Magarpatta is the major IT and business hub within Magarpatta City in Pune, India, housing numerous technology companies and corporate offices.
-
D.
Raheja IT Park
Raheja IT Park is a major commercial technology hub in Hyderabad’s HITEC City, housing numerous IT and software companies in a modern business campus.
-
E.
NESCO IT Park
NESCO IT Park is a major commercial and information technology hub in Goregaon, Mumbai, housing numerous corporate offices and tech companies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeea750c819082d8823c9ab6c5a2 |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae11d6648190bc9b5d4f520d694b |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:02 a.m.