Triple
T13382223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mall of Qatar |
E319344
|
entity |
| Predicate | numberOfRetailUnits |
P8902
|
FINISHED |
| Object | over 500 |
—
|
LITERAL 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: over 500 | Statement: [Mall of Qatar, numberOfRetailUnits, over 500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRetailUnits Context triple: [Mall of Qatar, numberOfRetailUnits, over 500]
-
A.
hasRetailUnits
Indicates that one entity possesses, operates, or is associated with one or more retail units (such as stores or outlets).
-
B.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
C.
numberOfRestaurantsAndRetail
Indicates the total count of entities that are either restaurants or retail establishments associated with a given subject.
-
D.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
E.
hasRetailStores
Indicates that an entity operates or possesses one or more physical retail store locations.
- F. None of above.
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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce694788190881d1feac5b75720 |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.