Triple
T11963156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ortigas MRT station |
E284720
|
entity |
| Predicate | locatedNearBoundary |
P55118
|
FINISHED |
| Object | Mandaluyong–Pasig boundary |
—
|
LITERAL 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: Mandaluyong–Pasig boundary | Statement: [Ortigas MRT station, locatedNearBoundary, Mandaluyong–Pasig boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedNearBoundary Context triple: [Ortigas MRT station, locatedNearBoundary, Mandaluyong–Pasig boundary]
-
A.
nearBorderBetween
chosen
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
-
C.
locatedInOrAdjacentTo
Indicates that one entity is either situated within the boundaries of another entity or directly next to it, sharing a common border or edge.
-
D.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
E.
liesOnBorderOf
Indicates that one entity is located along or directly adjacent to the boundary line separating it from another entity.
- F. None of above.
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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037848f481908276716675464464 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.