Triple
T7394687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foodpanda |
E170591
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Delivery Hero |
E661136
|
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: Delivery Hero | Statement: [Foodpanda, ownedBy, Delivery Hero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delivery Hero Context triple: [Foodpanda, ownedBy, Delivery Hero]
-
A.
Delivery Hero
chosen
Delivery Hero is a global online food delivery and quick-commerce company that operates numerous delivery platforms and brands across multiple countries.
-
B.
Deliveroo
Deliveroo is a British online food delivery company that partners with restaurants and couriers to deliver meals to customers via its app and website.
-
C.
DoorDash
DoorDash is a leading American on-demand food delivery and logistics platform that connects customers with local restaurants and merchants through its mobile app and website.
-
D.
Postmates
Postmates is an on-demand delivery service platform that connects users with local couriers to deliver food, groceries, and other goods from nearby merchants.
-
E.
GrabExpress
GrabExpress is Grab’s on-demand parcel and document delivery service operating across various Southeast Asian cities.
- 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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2279de4819081b8876d02f55388 |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81ecf65388190a149efc77aedcd91 |
completed | March 28, 2026, 6:32 p.m. |
Created at: March 27, 2026, 3:09 p.m.