Triple
T15645214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red House Theater |
E376159
|
entity |
| Predicate | accessibleBy |
P1017
|
FINISHED |
| Object | Ximen metro station |
E480441
|
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: Ximen metro station | Statement: [Red House Theater, accessibleBy, Ximen metro station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ximen metro station Context triple: [Red House Theater, accessibleBy, Ximen metro station]
-
A.
Los Orientales metro station
Los Orientales metro station is a public transit stop in Santiago, Chile, serving passengers on the city’s metro network near Avenida Tobalaba.
-
B.
Aigaleo metro station
Aigaleo metro station is an Athens Metro station serving the Aigaleo district in western Athens, Greece.
-
C.
San Babila Metro station
San Babila Metro station is a central Milan underground station serving the historic city core and providing access to major shopping and business areas.
-
D.
Shoush Metro Station
Shoush Metro Station is a stop on Tehran’s Metro system serving passengers along Line 1 in the Shoush neighborhood.
-
E.
Ximen Station
chosen
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed400ec8190a14a9f7cf3092865 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f4e558481909a39fdc5d104994a |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:15 a.m.