Triple
T25102690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asok Station |
E628773
|
entity |
| Predicate | nearShoppingArea |
P61270
|
FINISHED |
| Object | Sukhumvit retail corridor |
—
|
NE NERFINISHED |
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: Sukhumvit retail corridor | Statement: [Asok Station, nearShoppingArea, Sukhumvit retail corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearShoppingArea Context triple: [Asok Station, nearShoppingArea, Sukhumvit retail corridor]
-
A.
nearbyUse
Indicates that one entity uses or operates another entity that is located nearby or in close physical proximity.
-
B.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
locationOfShoppingCenter
Indicates that a specified place is the geographic location where a particular shopping center is situated.
-
E.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
- 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464be45448190b42c7d880d8550c8 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:26 a.m.