Triple
T12218302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JR West 207 series |
E291143
|
entity |
| Predicate | operatorCode |
P38995
|
FINISHED |
| Object | JR-W |
E955400
|
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: JR-W | Statement: [JR West 207 series, operatorCode, JR-W]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JR-W Context triple: [JR West 207 series, operatorCode, JR-W]
-
A.
JR
JR is a character from Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," which chronicles the lives and relationships of a diverse group of lesbian friends.
-
B.
JR
JR is the station code assigned to J. Ruiz station in the Manila Metro Rail Transit system.
-
C.
JR
chosen
JR is the common brand name and logo used by the Japan Railways Group, a network of major passenger and freight railway companies in Japan.
-
D.
JR
JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
-
E.
JW
JW is the IATA airline designator assigned to Vanilla Air, a former Japanese low-cost carrier.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c951f5881908db6edfda1153d6f |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa31f548190bd4f8cfe3c55614b |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:51 p.m.