Triple
T30411717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subang |
E773636
|
entity |
| Predicate | roadDistanceToKualaLumpurCityCentre_km |
P41771
|
FINISHED |
| Object | approximately 15–25 |
—
|
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: approximately 15–25 | Statement: [Subang, roadDistanceToKualaLumpurCityCentre_km, approximately 15–25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToKualaLumpurCityCentre_km Context triple: [Subang, roadDistanceToKualaLumpurCityCentre_km, approximately 15–25]
-
A.
distanceFromKualaLumpur
chosen
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
B.
distanceToAlorSetar_km
Indicates the distance, measured in kilometers, from a given location to Alor Setar.
-
C.
distanceFromKotaBharu
Indicates the spatial distance between an entity’s location and the city of Kota Bharu.
-
D.
distanceFromKuching
Indicates the spatial distance between a given location and Kuching.
-
E.
distanceToJohorBahruCityCentre
Indicates the spatial distance between an entity and the city center of Johor Bahru.
- 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_69f22490b8b48190ab10c886a8d58c89 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68646a420819096f45e8c037f8ac8 |
completed | May 2, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:05 p.m.