Triple
T8949126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chongqing Metro |
E213296
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Liziba Station
Liziba Station is a famous Chongqing Metro station known for its striking design where trains appear to pass directly through a residential building.
|
E850459
|
NE FINISHED |
How this triple was built (4 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: Liziba Station | Statement: [Chongqing Metro, hasStation, Liziba Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liziba Station Context triple: [Chongqing Metro, hasStation, Liziba Station]
-
A.
Sanda Station
Sanda Station is a railway station in Sanda, Hyōgo Prefecture, Japan, serving as a local transit hub on the JR West network.
-
B.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
-
C.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
D.
Chonu Station
Chonu Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Elichiribehety Station
Elichiribehety Station is a small Uruguayan Antarctic research base located at Hope Bay on the Antarctic Peninsula.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Liziba Station Triple: [Chongqing Metro, hasStation, Liziba Station]
Generated description
Liziba Station is a famous Chongqing Metro station known for its striking design where trains appear to pass directly through a residential building.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liziba Station Target entity description: Liziba Station is a famous Chongqing Metro station known for its striking design where trains appear to pass directly through a residential building.
-
A.
Sanda Station
Sanda Station is a railway station in Sanda, Hyōgo Prefecture, Japan, serving as a local transit hub on the JR West network.
-
B.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
-
C.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
D.
Chonu Station
Chonu Station is a stop on the Pyongyang Metro system in North Korea’s capital city.
-
E.
Elichiribehety Station
Elichiribehety Station is a small Uruguayan Antarctic research base located at Hope Bay on the Antarctic Peninsula.
- F. None of above. chosen
Provenance (5 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6709c7a48190ab503083a1d6a29f |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a75d16888190aad10857effd152d |
completed | April 8, 2026, 7:07 p.m. |
| NEDg | Description generation | batch_69d6aa57c19c81909611162d1d067da8 |
completed | April 8, 2026, 7:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6d02015bc8190a7041a7d725c8a1b |
completed | April 8, 2026, 10:01 p.m. |
Created at: March 30, 2026, 6:59 p.m.