Triple
T36077063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JGK |
E1043524
|
entity |
| Predicate | relatedStationNameChinese |
P112608
|
FINISHED |
| Object | 济南西站 |
E318294
|
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: 济南西站 | Statement: [JGK, relatedStationNameChinese, 济南西站]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedStationNameChinese Context triple: [JGK, relatedStationNameChinese, 济南西站]
-
A.
relatedStationNumber
Indicates that there is an associated or corresponding station identified by a particular station number.
-
B.
associatedStation
Indicates a relationship where one entity is linked or connected to a particular station as its relevant or related station.
-
C.
adjacentStationOnBeijingShanghaiHsr
Indicates that two stations are directly next to each other along the Beijing–Shanghai high-speed railway line, with no other station in between.
-
D.
nearbyStationName
chosen
Indicates that the predicate specifies the name of a station that is geographically close to a given reference point or entity.
-
E.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
- 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_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38d53e8dfc819095ae213a57f4b030 |
completed | June 22, 2026, 6:25 a.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.