Triple
T26894296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobabad |
E677858
|
entity |
| Predicate | distanceToQuettaApprox |
P180194
|
FINISHED |
| Object | about 300 km southeast |
—
|
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: about 300 km southeast | Statement: [Jacobabad, distanceToQuettaApprox, about 300 km southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToQuettaApprox Context triple: [Jacobabad, distanceToQuettaApprox, about 300 km southeast]
-
A.
distanceToQuettaApproximate
chosen
Indicates that an entity is located at an approximate distance from Quetta, rather than an exact measured distance.
-
B.
roadDistanceToQuettaInKilometres
Indicates the distance in kilometers between an entity and Quetta when traveling by road.
-
C.
distanceFromKarachi
Indicates the measured spatial distance between a given entity’s location and the city of Karachi.
-
D.
distanceFromIslamabad
Indicates the spatial distance between a given location and the city of Islamabad.
-
E.
distanceToLahore_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Lahore.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: April 27, 2026, 5:47 a.m.