Triple
T25253377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N-25 National Highway |
E632802
|
entity |
| Predicate | connectsProvinceToCountry |
P99274
|
FINISHED |
| Object | Balochistan |
—
|
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: Balochistan | Statement: [N-25 National Highway, connectsProvinceToCountry, Balochistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsProvinceToCountry Context triple: [N-25 National Highway, connectsProvinceToCountry, Balochistan]
-
A.
connectsProvinceOrRegion
Indicates that one entity serves to link or provide a connection between a specific province or region and another entity.
-
B.
connectsProvincesAlong
Indicates a relationship where something serves as a link or route joining multiple provinces along a specified path or alignment.
-
C.
connectsCountryOrRegion
chosen
Indicates that one entity establishes a connection, link, or association to a specific country or region.
-
D.
connectsStates
Indicates a relationship where one entity serves as a link or route that joins two or more states together.
-
E.
hasGeographicConnectionTo
Indicates a relationship where two entities are linked through a shared or relevant geographic feature, location, or spatial association.
- 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_69e75a8fdd3881909ba0b05aa5da92a7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 21, 2026, 1:11 p.m.