Triple
T20627990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lugazi |
E506870
|
entity |
| Predicate | hasCompany |
P1287
|
FINISHED |
| Object | Mehta Group |
—
|
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: Mehta Group | Statement: [Lugazi, hasCompany, Mehta Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mehta Group Context triple: [Lugazi, hasCompany, Mehta Group]
-
A.
Mehta Group
chosen
Mehta Group is a diversified Indian business conglomerate involved in sectors such as manufacturing, trading, and services.
-
B.
Shapoorji Pallonji Group
Shapoorji Pallonji Group is a major Indian conglomerate best known for its large-scale construction, infrastructure, and real estate businesses, with diversified interests across engineering, energy, and other sectors.
-
C.
Wadia Group
Wadia Group is one of India’s oldest conglomerates, with diversified interests spanning textiles, aviation, real estate, food, and chemicals.
-
D.
Oberoi Group
Oberoi Group is a prominent Indian luxury hospitality conglomerate best known for its high-end Oberoi and Trident hotel chains worldwide.
-
E.
Godrej Group
Godrej Group is a major Indian conglomerate with diversified interests spanning consumer goods, real estate, appliances, agriculture, and industrial engineering.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe645888190b639ebedc5b3041a |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.