Triple
T11679881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V. Mapa station |
E277586
|
entity |
| Predicate | precededByStation |
P29771
|
FINISHED |
| Object | Pureza station |
E277585
|
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: Pureza station | Statement: [V. Mapa station, precededByStation, Pureza station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pureza station Context triple: [V. Mapa station, precededByStation, Pureza station]
-
A.
Pureza station
chosen
Pureza station is an elevated rapid transit stop on Manila's LRT Line 2 serving the Santa Mesa area of the city.
-
B.
Gaiemmae Station
Gaiemmae Station is a Tokyo Metro subway station in Minato, Tokyo, serving the Ginza Line and providing convenient access to nearby sports and cultural facilities.
-
C.
Anonas station
Anonas station is an elevated rapid transit stop on Manila’s Light Rail Transit Line 2 serving the Quezon City area.
-
D.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
E.
Prujakan Station
Prujakan Station is a railway station in Cirebon, Indonesia, serving as one of the city’s key stops for regional and intercity train services.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a461b0908190bef4e1c6777affcf |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83098e2c819081c22462372f64b4 |
completed | April 27, 2026, 3:38 p.m. |
Created at: April 8, 2026, 9:40 p.m.