Triple
T30111992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolivar (Paris Métro) |
E765301
|
entity |
| Predicate | adjacentStationOnLine 7bis |
P41425
|
FINISHED |
| Object | Buttes Chaumont (Paris Métro) |
—
|
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: Buttes Chaumont (Paris Métro) | Statement: [Bolivar (Paris Métro), adjacentStationOnLine 7bis, Buttes Chaumont (Paris Métro)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnLine 7bis Context triple: [Bolivar (Paris Métro), adjacentStationOnLine 7bis, Buttes Chaumont (Paris Métro)]
-
A.
hasAdjacentStationOnLine 7bis
Indicates that one station is directly next to another station along metro line 7bis.
-
B.
adjacentStationOnLine
chosen
Indicates that one station is directly next to another station along the same transit line, with no other station in between.
-
C.
adjacentStationOnLine2
Indicates that one station is directly next to another station along line 2 in a transit or rail network.
-
D.
adjacentStationOnLineD
Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
-
E.
adjacentStationOnLineB
Indicates that one station is directly next to another station along line B in the network.
- F. None of above.
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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 29, 2026, 7:10 p.m.