Triple
T4536755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makati |
E107424
|
entity |
| Predicate | hasRailStation |
P726
|
FINISHED |
| Object | Buendia station |
E297312
|
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: Buendia station | Statement: [Makati, hasRailStation, Buendia station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buendia station Context triple: [Makati, hasRailStation, Buendia station]
-
A.
Buendia station
chosen
Buendia station is an elevated rapid transit stop on Manila's MRT Line 3 serving the busy Buendia Avenue area in Makati, Philippines.
-
B.
Pino Suárez station
Pino Suárez station is a major Mexico City Metro interchange hub located in the historic center, connecting multiple lines and serving as a key transit point for commuters.
-
C.
Retiro station
Retiro station is a major Buenos Aires Underground terminus and transport hub located in the Retiro district of Argentina’s capital.
-
D.
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.
-
E.
Santiago Bueras station
Santiago Bueras station is an underground stop on Santiago’s Metro network serving Line 5 in the western part of the city.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc55ae8248190acda4f10eb5ce2e7 |
completed | March 20, 2026, 10:08 p.m. |
Created at: March 20, 2026, 1:04 p.m.