Triple
T28500536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shilin Karst |
E721217
|
entity |
| Predicate | distanceFromKunming |
P85493
|
FINISHED |
| Object | approximately 80 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 80 kilometers | Statement: [Shilin Karst, distanceFromKunming, approximately 80 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKunming Context triple: [Shilin Karst, distanceFromKunming, approximately 80 kilometers]
-
A.
distanceToKunming
chosen
Indicates the spatial distance between a given location or entity and the city of Kunming.
-
B.
distanceFromBogotá
Indicates the spatial distance separating a given entity or location from the city of Bogotá.
-
C.
distanceFromMedellín
Indicates the measured spatial distance between an entity and the city of Medellín.
-
D.
approximateDistanceInKilometersFromChiangMai
Indicates the approximate physical distance, measured in kilometers, between a given entity’s location and Chiang Mai.
-
E.
distanceToSantaMarta
Indicates the measured spatial distance between a given entity’s location and the location of Santa Marta.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_6a001540d4f881908a4688881875e774 |
completed | May 10, 2026, 5:18 a.m. |
| PD | Predicate disambiguation | batch_6a0014a8cdd88190a67a90a2df2c5e18 |
completed | May 10, 2026, 5:16 a.m. |
Created at: April 28, 2026, 3:06 a.m.