Triple
T7346487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GrabFood |
E169392
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Foodpanda |
E170591
|
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: Foodpanda | Statement: [GrabFood, competesWith, Foodpanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Foodpanda Context triple: [GrabFood, competesWith, Foodpanda]
-
A.
Foodpanda
chosen
Foodpanda is an online food and grocery delivery platform operating across multiple countries, connecting customers with restaurants and shops via its app and website.
-
B.
GrabFood
GrabFood is a Southeast Asian on-demand food delivery service integrated into the Grab super app, connecting users with restaurants and couriers for meal orders and delivery.
-
C.
Uber Eats
Uber Eats is an online food delivery platform operated by Uber that connects users with local restaurants and couriers for on-demand meal delivery.
-
D.
Coupang Eats
Coupang Eats is a South Korean food delivery platform operated by e-commerce giant Coupang, offering on-demand meal ordering from local restaurants.
-
E.
ShopeeFood
ShopeeFood is an online food delivery platform operated by Shopee that connects users with restaurants and couriers through its mobile app and website.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0f0329c8190a0182e3bf62604e5 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa916ac881909acee8184b71dc85 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:05 p.m.