Triple
T37601468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SM Supermalls |
E935534
|
entity |
| Predicate | hasOverseasMall |
P16039
|
FINISHED |
| Object |
SM City Xiamen
SM City Xiamen is a large Philippine-owned shopping mall complex located in Xiamen, China, operated by the SM Supermalls chain as one of its overseas developments.
|
E1873706
|
NE FINISHED |
How this triple was built (3 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: SM City Xiamen | Statement: [SM Supermalls, hasOverseasMall, SM City Xiamen]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SM City Xiamen Triple: [SM Supermalls, hasOverseasMall, SM City Xiamen]
Generated description
SM City Xiamen is a large Philippine-owned shopping mall complex located in Xiamen, China, operated by the SM Supermalls chain as one of its overseas developments.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOverseasMall Context triple: [SM Supermalls, hasOverseasMall, SM City Xiamen]
-
A.
hasOverseasPresenceIn
Indicates that an entity maintains operations, offices, or activities in a foreign country or region.
-
B.
hasShoppingMall
chosen
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
C.
overseasIncludes
Indicates that one entity geographically or administratively encompasses another entity located in a foreign or overseas region.
-
D.
hasOnlineShop
Indicates that an entity operates or is associated with a shop that sells goods or services via the internet.
-
E.
hasShop
Indicates that one entity owns, operates, or is associated with a shop or retail establishment.
- F. None of above.
Provenance (6 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40a80687c88190abab7c749bd61479 |
completed | June 28, 2026, 4:50 a.m. |
| NEDg | Description generation | batch_6a40a87e4c008190b9a9c54dd789dbc2 |
completed | June 28, 2026, 4:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40a901f21c8190ad963f201863a3b0 |
completed | June 28, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.