Triple
T12138138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Tambuyukon |
E289113
|
entity |
| Predicate | distanceToMountKinabalu |
P103579
|
FINISHED |
| Object | about 12 km north |
—
|
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 12 km north | Statement: [Mount Tambuyukon, distanceToMountKinabalu, about 12 km north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMountKinabalu Context triple: [Mount Tambuyukon, distanceToMountKinabalu, about 12 km north]
-
A.
distanceFromKotaBharu
Indicates the spatial distance between an entity’s location and the city of Kota Bharu.
-
B.
distanceFromKualaLumpur
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
C.
distanceToSummit
Indicates the measured or estimated distance remaining from a given point to the summit of a feature or elevation.
-
D.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
-
E.
distanceToDenali
Indicates the measured or estimated spatial distance between a given entity and Denali.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9183ec1008190b437b7d5e1f52830 |
completed | April 10, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:49 p.m.