Triple
T32801076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serdang, Selangor, Malaysia |
E838896
|
entity |
| Predicate | distanceToKualaLumpurApprox |
P41771
|
FINISHED |
| Object | about 20 km south of Kuala Lumpur city centre |
—
|
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 20 km south of Kuala Lumpur city centre | Statement: [Serdang, Selangor, Malaysia, distanceToKualaLumpurApprox, about 20 km south of Kuala Lumpur city centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKualaLumpurApprox Context triple: [Serdang, Selangor, Malaysia, distanceToKualaLumpurApprox, about 20 km south of Kuala Lumpur city centre]
-
A.
distanceFromKualaLumpur
chosen
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
B.
distanceToKLIA
Indicates the measured distance between a given location and Kuala Lumpur International Airport (KLIA).
-
C.
distanceToAlorSetar_km
Indicates the distance, measured in kilometers, from a given location to Alor Setar.
-
D.
distanceFromMalaysia
Indicates the measured spatial distance between a given entity and the country of Malaysia.
-
E.
distanceFromKuching
Indicates the spatial distance between a given location and Kuching.
- 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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:14 a.m.