Triple
T33971687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Montpellier |
E871013
|
entity |
| Predicate | terminusCityRole |
P185252
|
FINISHED |
| Object | Paris is the capital of France |
—
|
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: Paris is the capital of France | Statement: [Paris–Montpellier, terminusCityRole, Paris is the capital of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terminusCityRole Context triple: [Paris–Montpellier, terminusCityRole, Paris is the capital of France]
-
A.
terminusCity
Indicates that a transportation route or service ends or has its final stop in a particular city.
-
B.
terminusConnectsTo
Indicates that a transportation route’s endpoint is directly linked or transitions to another route, line, or terminal.
-
C.
terminusCitySouthwest
Indicates that the terminus (end point) of something is located to the southwest of a specified city.
-
D.
terminusCityArea
Indicates that a city area serves as the terminal or end-point location for a route, line, or journey.
-
E.
terminusCityWest
Indicates that a route, line, or service has its western terminus located in the specified city.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 1, 2026, 1:50 a.m.