Triple
T8862951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandaluyong |
E210936
|
entity |
| Predicate | hasRailStation |
P726
|
FINISHED |
| Object | Ortigas station |
E297311
|
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: Ortigas station | Statement: [Mandaluyong, hasRailStation, Ortigas station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ortigas station Context triple: [Mandaluyong, hasRailStation, Ortigas station]
-
A.
Ortigas station
chosen
Ortigas station is an elevated rapid transit stop serving the Ortigas Center business district in Metro Manila, Philippines.
-
B.
Antipolo station
Antipolo station is an elevated eastern terminal station of Manila’s LRT Line 2 serving the city of Antipolo in Rizal, Philippines.
-
C.
Pío Nono station
Pío Nono station is a lower terminal of Santiago’s historic funicular railway that provides access to San Cristóbal Hill in Chile.
-
D.
Legazpi metro station
Legazpi metro station is a Madrid Metro station in the Arganzuela district that serves as a key access point to nearby cultural sites such as Matadero Madrid.
-
E.
Ayala station
Ayala station is a major elevated rapid transit stop on Manila's MRT Line 3 serving the busy Makati Central Business District in the Philippines.
- 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_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_69cfc1c3c6c08190b51ea5e9cf7085e9 |
completed | April 3, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:50 p.m.