Triple
T188754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singapore |
E3670
|
entity |
| Predicate | cityStatus |
P3206
|
FINISHED |
| Object | global city |
—
|
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: global city | Statement: [Singapore, cityStatus, global city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityStatus Context triple: [Singapore, cityStatus, global city]
-
A.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
B.
city1
chosen
Indicates that the subject is classified as a city.
-
C.
cityPanorama
Indicates a wide, comprehensive visual view or representation of a cityscape, typically encompassing many of its features in a single scene.
-
D.
primaryCity
Indicates that one city serves as the main or most important city associated with a given region, entity, or context.
-
E.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594abeec8190a48f36817e647fcd |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.