Triple
T17324342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohammed V International Airport |
E420646
|
entity |
| Predicate | distanceFromCasablanca |
P126776
|
FINISHED |
| Object | approximately 30 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: approximately 30 km southeast | Statement: [Mohammed V International Airport, distanceFromCasablanca, approximately 30 km southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCasablanca Context triple: [Mohammed V International Airport, distanceFromCasablanca, approximately 30 km southeast]
-
A.
distanceFromMarrakesh
Indicates the spatial distance between a given location and the city of Marrakesh.
-
B.
distanceToTunis
Indicates the spatial distance between a given entity’s location and the city of Tunis.
-
C.
hasApproximateDirectionFromCasablanca
chosen
Indicates that one entity is located in a direction that is only roughly or loosely specified relative to Casablanca.
-
D.
distanceFromDakar
Indicates the spatial distance between a given entity’s location and the city of Dakar.
-
E.
distanceFromSanaa
Indicates the spatial distance between an entity and the location of Sanaa.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d18e3081908ca15baa743abcd8 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.