Triple
T36058173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuala Lumpur International Airport ERL station |
E1043003
|
entity |
| Predicate | travelTimeToKLsentral |
P185286
|
FINISHED |
| Object | about 28 minutes by KLIA Ekspres |
—
|
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: about 28 minutes by KLIA Ekspres | Statement: [Kuala Lumpur International Airport ERL station, travelTimeToKLsentral, about 28 minutes by KLIA Ekspres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeToKLsentral Context triple: [Kuala Lumpur International Airport ERL station, travelTimeToKLsentral, about 28 minutes by KLIA Ekspres]
-
A.
travelTimeFromKotaKinabalu
Indicates the amount of time required to travel from Kota Kinabalu to another specified location or entity.
-
B.
distanceFromKualaLumpur
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
C.
distanceToAlorSetar_km
Indicates the distance, measured in kilometers, from a given location to Alor Setar.
-
D.
distanceToJohorBahruCityCentre
Indicates the spatial distance between an entity and the city center of Johor Bahru.
-
E.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 3, 2026, 4:08 p.m.