Triple
T4627723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mytishchi |
E101138
|
entity |
| Predicate | roadDistanceFromMoscowCenter_km |
P24098
|
FINISHED |
| Object | approximately 25 |
—
|
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 | Statement: [Mytishchi, roadDistanceFromMoscowCenter_km, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceFromMoscowCenter_km Context triple: [Mytishchi, roadDistanceFromMoscowCenter_km, approximately 25]
-
A.
distanceFromMoscow_km
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
B.
frontLineDistanceFromMoscow
Indicates the measured distance between the current front line of a conflict and the city of Moscow.
-
C.
distanceToArkhangelskApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Arkhangelsk.
-
D.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
E.
distanceFromSamarkand_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Samarkand.
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a2e9780819081add547c760abc9 |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.