Triple
T22242662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singaraja |
E549760
|
entity |
| Predicate | distanceFromDenpasar |
P147516
|
FINISHED |
| Object | approximately 80–90 km |
—
|
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 80–90 km | Statement: [Singaraja, distanceFromDenpasar, approximately 80–90 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDenpasar Context triple: [Singaraja, distanceFromDenpasar, approximately 80–90 km]
-
A.
distanceFromNgurahRaiAirport
Indicates the measured distance between a given location and Ngurah Rai Airport.
-
B.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
-
C.
distanceFromUbud
Indicates the spatial distance separating a given place or object from the location of Ubud.
-
D.
distanceToMataram
Indicates the measured spatial distance between a given entity’s location and the location of Mataram.
-
E.
distanceToPrambanan
Indicates the spatial distance between an entity and the location of Prambanan.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f132150a3c81908eba0683819e26d0 |
completed | April 28, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:38 p.m.