Triple
T37278722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemins de fer de l'État |
E925319
|
entity |
| Predicate | primaryLines |
P159027
|
FINISHED |
| Object | Paris–Le Mans–Rennes–Brest line |
E256048
|
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: Paris–Le Mans–Rennes–Brest line | Statement: [Chemins de fer de l'État, primaryLines, Paris–Le Mans–Rennes–Brest line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLines Context triple: [Chemins de fer de l'État, primaryLines, Paris–Le Mans–Rennes–Brest line]
-
A.
primaryTrunkLine
chosen
Indicates a relationship where one line functions as the main or principal trunk route among a set of connected lines.
-
B.
secondaryLine
Indicates that something serves as a secondary or auxiliary line in relation to a primary or main line.
-
C.
firstLines
Indicates that one text, segment, or element constitutes the initial lines or opening portion of another.
-
D.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
E.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
- F. None of above.
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_69f76eafe20c8190856d3b996a4c31a7 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a405139b2dc8190b17268f0b3cf2489 |
completed | June 27, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.