Triple
T35897759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rammang-Rammang karst area |
E1038270
|
entity |
| Predicate | distanceFromMakassar |
P206098
|
FINISHED |
| Object | approximately 40 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 40 kilometers | Statement: [Rammang-Rammang karst area, distanceFromMakassar, approximately 40 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMakassar Context triple: [Rammang-Rammang karst area, distanceFromMakassar, approximately 40 kilometers]
-
A.
distanceFromDenpasar
Indicates the spatial distance between a given location and Denpasar.
-
B.
distanceToSamarinda_km
Indicates the physical distance, measured in kilometers, between a given location and Samarinda.
-
C.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
-
D.
distanceToMataram
Indicates the measured spatial distance between a given entity’s location and the location of Mataram.
-
E.
distanceFromMasaka_km
Indicates the physical distance, measured in kilometers, between an entity and the location Masaka.
- 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_69f76e2190f88190beb2eed798a4ef01 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037ce53de881908cf14141cf3bc570 |
completed | May 12, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:07 p.m.