Triple
T29127409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moret–Lyon railway |
E738269
|
entity |
| Predicate | formerMainRouteBetween |
P196780
|
FINISHED |
| Object | Paris |
—
|
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: Paris | Statement: [Moret–Lyon railway, formerMainRouteBetween, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerMainRouteBetween Context triple: [Moret–Lyon railway, formerMainRouteBetween, Paris]
-
A.
primaryRouteThrough
Indicates that one location or path serves as the main or most significant route passing through another location or area.
-
B.
formerRouteNumber
Indicates that an entity previously had a specific route number before being renumbered, discontinued, or otherwise changed.
-
C.
usesFormerRouteOf
Indicates that one route, service, or pathway currently follows all or part of the alignment or path that was previously used by another route.
-
D.
majorRouteTo
Indicates that one location serves as a primary or significant route or pathway leading to another location.
-
E.
routeOf
Indicates that one entity is the path, course, or trajectory taken or followed by another entity (such as a vehicle, shipment, or signal).
- F. None of above. chosen
Provenance (4 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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
| PDg | Predicate description generation | batch_69fe68a385f48190b942700e3eddc9b6 |
completed | May 8, 2026, 10:50 p.m. |
Created at: April 28, 2026, 11:29 a.m.