Triple
T22118330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Hall MRT station |
E546596
|
entity |
| Predicate | hasRetailOutlets |
P87312
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [City Hall MRT station, hasRetailOutlets, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailOutlets Context triple: [City Hall MRT station, hasRetailOutlets, yes]
-
A.
hasRetailStores
chosen
Indicates that an entity operates or possesses one or more physical retail store locations.
-
B.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
C.
hasOutletStores
Indicates that an entity operates or is associated with one or more outlet retail stores.
-
D.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
-
E.
hasRetailNetwork
Indicates that an entity operates or is associated with a system of retail outlets or distribution channels through which products or services are sold.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294fcf2c81909b610e03a0f1921f |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:31 p.m.