Triple
T12769321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yas Mall |
E305203
|
entity |
| Predicate | hasTenant |
P3277
|
FINISHED |
| Object | Carrefour |
E131992
|
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: Carrefour | Statement: [Yas Mall, hasTenant, Carrefour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carrefour Context triple: [Yas Mall, hasTenant, Carrefour]
-
A.
Carrefour
chosen
Carrefour is a major French multinational retail corporation and one of the world’s largest hypermarket chains.
-
B.
Carrefour
Carrefour is a major suburban city in Haiti, located just southwest of the capital Port-au-Prince and known as part of the country's largest metropolitan area.
-
C.
Auchan hypermarket
Auchan hypermarket is a major French multinational retail chain of large-format supermarkets offering a wide range of groceries, household goods, and general merchandise.
-
D.
Kaufhof
Kaufhof was a major German department store chain that later became part of the Galeria Kaufhof brand.
-
E.
Tesco
Tesco is a major British multinational grocery and general merchandise retailer and one of the largest supermarket chains in the world.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df3b2f88190b37b696400178795 |
completed | April 10, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f9ba848190b680d730b6a3b972 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:28 p.m.