Triple
T25460876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parangtritis Beach |
E638041
|
entity |
| Predicate | distanceFromYogyakartaCity |
P126287
|
FINISHED |
| Object | about 25–30 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: about 25–30 kilometers | Statement: [Parangtritis Beach, distanceFromYogyakartaCity, about 25–30 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromYogyakartaCity Context triple: [Parangtritis Beach, distanceFromYogyakartaCity, about 25–30 kilometers]
-
A.
distanceFromYogyakarta
chosen
Indicates the spatial distance between a given place or object and the location of Yogyakarta.
-
B.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
-
C.
distanceFromDenpasar
Indicates the spatial distance between a given location and Denpasar.
-
D.
distanceToPrambanan
Indicates the spatial distance between an entity and the location of Prambanan.
-
E.
distanceToSamarinda_km
Indicates the physical distance, measured in kilometers, between a given location and Samarinda.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: April 21, 2026, 2:12 p.m.