Triple
T8862949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandaluyong |
E210936
|
entity |
| Predicate | hasRailStation |
P726
|
FINISHED |
| Object |
Boni station
Boni station is an elevated rapid transit station on Manila's MRT Line 3 serving the city of Mandaluyong in the Philippines.
|
E770848
|
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: Boni station | Statement: [Mandaluyong, hasRailStation, Boni station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boni station Context triple: [Mandaluyong, hasRailStation, Boni station]
-
A.
Anonas station
Anonas station is an elevated rapid transit stop on Manila’s Light Rail Transit Line 2 serving the Quezon City area.
-
B.
Cabitos station
Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
-
C.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
-
D.
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.
-
E.
Batutulis Station
Batutulis Station is a small railway station in Bogor, West Java, Indonesia, serving local commuter and regional train services on the line south of Bogor.
- 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: Boni station Triple: [Mandaluyong, hasRailStation, Boni station]
Generated description
Boni station is an elevated rapid transit station on Manila's MRT Line 3 serving the city of Mandaluyong in the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Boni station Target entity description: Boni station is an elevated rapid transit station on Manila's MRT Line 3 serving the city of Mandaluyong in the Philippines.
-
A.
Anonas station
Anonas station is an elevated rapid transit stop on Manila’s Light Rail Transit Line 2 serving the Quezon City area.
-
B.
Cabitos station
Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
-
C.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
-
D.
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.
-
E.
Batutulis Station
Batutulis Station is a small railway station in Bogor, West Java, Indonesia, serving local commuter and regional train services on the line south of Bogor.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc610263048190931bb2c3ac573a08 |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd082bbe88190a207d39f9295735e |
completed | April 3, 2026, 2:36 p.m. |
| NEDg | Description generation | batch_69cfd1e8a5f8819092fe8a91d4d53697 |
completed | April 3, 2026, 2:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfd242590881909ca351c1040c76ef |
completed | April 3, 2026, 2:44 p.m. |
Created at: March 30, 2026, 6:50 p.m.