Triple
T12500445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silom Line |
E298804
|
entity |
| Predicate | connectsCommercialArea |
P75875
|
FINISHED |
| Object | Siam commercial area |
—
|
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: Siam commercial area | Statement: [Silom Line, connectsCommercialArea, Siam commercial area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCommercialArea Context triple: [Silom Line, connectsCommercialArea, Siam commercial area]
-
A.
connectsCommercialAreas
Indicates a relationship where one entity links or provides direct access between two or more commercial areas or business districts.
-
B.
connectsToCommercialArea
chosen
Indicates that one location has a direct link, route, or access path to a commercial area.
-
C.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
D.
connectsResidentialArea
Indicates a relationship where something serves as a link or route between one residential area and another.
-
E.
commercialArea
Indicates that the location or region is designated primarily for commercial activities such as businesses, shops, or services.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:57 p.m.