Triple
T11040991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adigrat |
E261013
|
entity |
| Predicate | roadDistanceToAsmara |
P97444
|
FINISHED |
| Object | approximately 230 kilometres |
—
|
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: approximately 230 kilometres | Statement: [Adigrat, roadDistanceToAsmara, approximately 230 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToAsmara Context triple: [Adigrat, roadDistanceToAsmara, approximately 230 kilometres]
-
A.
distanceFromBahirDar
Indicates the spatial distance separating a given entity or location from Bahir Dar.
-
B.
distanceFromSanaa
Indicates the spatial distance between an entity and the location of Sanaa.
-
C.
timeToReachNearKhartoum
Indicates the amount of time required for an entity to arrive at or near the location of Khartoum.
-
D.
distanceToArusha
Indicates the measured spatial distance between a given entity and the location Arusha.
-
E.
distanceToTripoli_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Tripoli.
- F. None of above. chosen
Provenance (4 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7980050948190ae7b187da5b776ca |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:26 p.m.