Triple
T22475396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarke Quay MRT station |
E555614
|
entity |
| Predicate | hasUnpaidArea |
P39724
|
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: [Clarke Quay MRT station, hasUnpaidArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnpaidArea Context triple: [Clarke Quay MRT station, hasUnpaidArea, yes]
-
A.
isUnpaid
Indicates that an expected payment, fee, or financial obligation has not yet been made or settled.
-
B.
hasUnorganizedArea
Indicates that an entity possesses or includes an area that lacks formal organization, structure, or systematic arrangement.
-
C.
isUnpaidOffice
Indicates that an office or position is held without financial compensation or salary.
-
D.
hasAllotmentArea
Indicates that an entity is associated with a specific area of land that has been formally allotted or assigned to it.
-
E.
hasPayStatus
chosen
Indicates the current payment state or condition associated with an entity, such as whether an amount is paid, unpaid, pending, or otherwise resolved.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be3930c8190ba967196df7e083f |
completed | April 29, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.