Triple
T6308443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avachinsky volcano |
E141436
|
entity |
| Predicate | distanceToPetropavlovskKamchatsky |
P69977
|
FINISHED |
| Object | approximately 25 km |
—
|
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 25 km | Statement: [Avachinsky volcano, distanceToPetropavlovskKamchatsky, approximately 25 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPetropavlovskKamchatsky Context triple: [Avachinsky volcano, distanceToPetropavlovskKamchatsky, approximately 25 km]
-
A.
distanceToArkhangelskApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Arkhangelsk.
-
B.
distanceToYakutsk
Indicates the spatial distance between a given entity and the location of Yakutsk.
-
C.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
D.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
E.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647d38008190abaf96632712ddf9 |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:28 p.m.