Triple
T20974454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lembar Harbour |
E516587
|
entity |
| Predicate | distanceToMataram |
P142318
|
FINISHED |
| Object | approximately 20–25 kilometers |
—
|
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 20–25 kilometers | Statement: [Lembar Harbour, distanceToMataram, approximately 20–25 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMataram Context triple: [Lembar Harbour, distanceToMataram, approximately 20–25 kilometers]
-
A.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
-
B.
distanceToPrambanan
Indicates the spatial distance between an entity and the location of Prambanan.
-
C.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
-
D.
distanceFromYogyakarta
Indicates the spatial distance between a given place or object and the location of Yogyakarta.
-
E.
distanceFromNgurahRaiAirport
Indicates the measured distance between a given location and Ngurah Rai Airport.
- 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_69e0b4fee5ac8190875fa9ceba1a5e5e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fba307d88190b728544d1b6d0bb6 |
completed | April 21, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 1:46 p.m.