Triple
T15065721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DLF Mega Mall |
E379749
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | DLF Limited |
E1072757
|
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 Limited | Statement: [DLF Mega Mall, owner, DLF Limited]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DLF Limited Context triple: [DLF Mega Mall, owner, DLF Limited]
-
A.
DLF
chosen
DLF is a major Indian real estate company that gained widespread recognition as the inaugural title sponsor of the Indian Premier League (IPL).
-
B.
Godrej Properties Limited
Godrej Properties Limited is a major Indian real estate development company and part of the diversified Godrej Group conglomerate.
-
C.
K Raheja Corp
K Raheja Corp is a prominent Indian real estate and property development company known for developing large commercial, residential, and IT park projects across major cities.
-
D.
Mehta Group
Mehta Group is a diversified Indian business conglomerate involved in sectors such as manufacturing, trading, and services.
-
E.
DLF Cyber Greens
DLF Cyber Greens is a prominent commercial office complex in Gurugram’s Cyber City business district, housing numerous multinational corporations and technology 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_69feb7dd767c8190a129f00303f970bc |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:02 a.m.