Triple
T2677769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRT Line 3 |
E56499
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Boni station |
E284719
|
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: Boni station | Statement: [MRT Line 3, hasStation, Boni station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boni station Context triple: [MRT Line 3, hasStation, Boni station]
-
A.
Recto station
Recto station is an elevated terminal station of Manila’s LRT Line 2 located in the busy commercial district of Recto Avenue in the Philippines.
-
B.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
C.
Namba Station
Namba Station is one of Osaka’s major railway and subway terminals, serving as a key commercial and transportation hub in the city’s bustling Namba district.
-
D.
Boni MRT station
chosen
Boni MRT station is an elevated rapid transit station on Manila's MRT Line 3 serving the city of Mandaluyong in Metro Manila, Philippines.
-
E.
Kitasando Station
Kitasando Station is an underground subway station in Shibuya, Tokyo, serving the Tokyo Metro network near the Meiji Shrine and Harajuku area.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9b697fc8190a5ec8b75ee2ad238 |
completed | March 7, 2026, 7:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6382a2081909ea7216c19a65e7e |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:54 p.m.