Triple
T6865576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-125 Neva/Pechora |
E158391
|
entity |
| Predicate | typicalEngagementRange_km |
P61967
|
FINISHED |
| Object | 3–25 |
—
|
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: 3–25 | Statement: [S-125 Neva/Pechora, typicalEngagementRange_km, 3–25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEngagementRange_km Context triple: [S-125 Neva/Pechora, typicalEngagementRange_km, 3–25]
-
A.
engagementRange
chosen
Indicates the distance or span within which an entity can effectively engage, interact with, or affect another entity.
-
B.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
-
C.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
D.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
E.
typicalEnergyRange
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6da3ce95081909a424ac04bc7fa07 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b168908190b2f7c724b1bc7fc9 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:21 p.m.