Triple
T24535269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raffles City Chengdu |
E606931
|
entity |
| Predicate | hasNumberOfUses |
P156641
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Raffles City Chengdu, hasNumberOfUses, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfUses Context triple: [Raffles City Chengdu, hasNumberOfUses, multiple]
-
A.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
B.
areUsedSince
Indicates that entities have been in use continuously starting from a specified point in time.
-
C.
hasPartUsed
Indicates that an entity utilizes another entity as a component or constituent part in its structure, function, or operation.
-
D.
hasPresentUse
Indicates that an entity is currently being used or serving a particular function at the present time.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- F. None of above. chosen
Provenance (4 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:26 a.m.