Triple
T8739706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tumpat |
E207469
|
entity |
| Predicate | distanceFromKotaBharu |
P84584
|
FINISHED |
| Object | about 20–25 km northwest |
—
|
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 20–25 km northwest | Statement: [Tumpat, distanceFromKotaBharu, about 20–25 km northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKotaBharu Context triple: [Tumpat, distanceFromKotaBharu, about 20–25 km northwest]
-
A.
distanceFromKualaLumpur
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
B.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
-
C.
distanceFromBangkok
Indicates the spatial distance between a given location and the city of Bangkok.
-
D.
nearCityOnMalaysianSide
Indicates that one entity is located close to a particular city that lies on the Malaysian side of a border or region.
-
E.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d486e34819094a6c6ec26c047cf |
completed | March 31, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:38 p.m.