Triple
T20672658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M3 motorway (Hungary) |
E508068
|
entity |
| Predicate | routeNumber |
P1864
|
FINISHED |
| Object | M3 |
—
|
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: M3 | Statement: [M3 motorway (Hungary), routeNumber, M3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M3 Context triple: [M3 motorway (Hungary), routeNumber, M3]
-
A.
M3
M3 is a major motorway in the United Kingdom that connects London to Southampton, serving as a key route through southern England.
-
B.
M3
M3 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s lake or waterways.
-
C.
M3
M3 is one of the main lines of the Bucharest Metro rapid transit system, serving key residential and commercial areas of Romania’s capital.
-
D.
M3
M3 is a NASA-designed imaging spectrometer that flew on India's Chandrayaan-1 lunar mission to map the Moon’s surface mineralogy and detect water and hydroxyl signatures.
-
E.
M3
chosen
M3 is the third line of the Budapest Metro system, running in a north–south direction and serving as one of the city’s main rapid transit corridors.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5cb1fc88190805f623e93a70368 |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.