Triple
T16697779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Istra |
E405759
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | M9 highway |
—
|
NE NERFINISHED |
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: M9 highway | Statement: [Istra, hasTransportConnection, M9 highway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M9 highway Context triple: [Istra, hasTransportConnection, M9 highway]
-
A.
M9 highway
chosen
The M9 highway is a major Russian federal road that connects Moscow with the Latvian border, forming part of the route toward Riga and the Baltic region.
-
B.
M8 highway
The M8 highway is a major Russian federal road that runs northeast from Moscow toward Yaroslavl and Arkhangelsk, forming part of an important transport corridor to the Russian North.
-
C.
M2 highway
The M2 highway is a major Russian federal road that runs south from Moscow toward the border with Ukraine, forming part of the route to cities like Tula and Kursk.
-
D.
M11 highway
The M11 highway is a major Russian toll motorway connecting Moscow and Saint Petersburg, serving as a key high-speed transport corridor in northwestern Russia.
-
E.
M10 highway
The M10 highway is a major Russian federal road that connects Moscow and Saint Petersburg, passing through cities such as Tver.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3832e93c48190a594c498e9cc901a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:19 a.m.