Triple
T28111672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Channel 4 (VHF, Metro Manila) |
E710505
|
entity |
| Predicate | signalCoverageArea |
P19200
|
FINISHED |
| Object | Greater Manila Area |
—
|
NE NERFINISHED |
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: Greater Manila Area | Statement: [Channel 4 (VHF, Metro Manila), signalCoverageArea, Greater Manila Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signalCoverageArea Context triple: [Channel 4 (VHF, Metro Manila), signalCoverageArea, Greater Manila Area]
-
A.
networkCoverage
Indicates the extent to which a network’s signal or service is available across a given area or to specific entities.
-
B.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
-
C.
regionCoverage
chosen
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
D.
sensorCoverage
Indicates that a sensor’s detection or monitoring area spatially covers or includes a given region, object, or point.
-
E.
hasCoveringRadius
Indicates the maximum distance from any point in a space to the nearest point in a given set, defining how well that set covers the space.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 9:11 p.m.