Triple
T7201106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-3 highway |
E168745
|
entity |
| Predicate | routeNumber |
P1864
|
FINISHED |
| Object | M-3 |
E648755
|
NE 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: M-3 | Statement: [M-3 highway, routeNumber, M-3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M-3 Context triple: [M-3 highway, routeNumber, M-3]
-
A.
M-3
chosen
M-3 is a designated highway route, commonly known by its short name M-3, within a regional or national road network.
-
B.
M-39
M-39 is a state highway in Michigan commonly known as the Southfield Freeway, serving as a major north–south commuter route in the Detroit metropolitan area.
-
C.
M-37
M-37 is a state highway in Michigan that runs up the Old Mission Peninsula, providing scenic access between Traverse City and the peninsula’s vineyards, orchards, and shoreline.
-
D.
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.
-
E.
M3
M3 is a circular line of the Copenhagen Metro that loops around the city center, connecting key districts and interchange stations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94971508190bb38184c9af2fe51 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cbecb7ec819080b12a63dfa56328 |
completed | March 28, 2026, 12:39 p.m. |
Created at: March 27, 2026, 2:52 p.m.