Triple
T783111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxor |
E16540
|
entity |
| Predicate | distanceFromCairo |
P19576
|
FINISHED |
| Object | approximately 650 km south |
—
|
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 650 km south | Statement: [Luxor, distanceFromCairo, approximately 650 km south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCairo Context triple: [Luxor, distanceFromCairo, approximately 650 km south]
-
A.
distanceFromJerusalem
Indicates the spatial distance between a given location and Jerusalem.
-
B.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
C.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
D.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
E.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7686d0881908c2a4395059be02c |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a67e69288190b3dc278c5bd94155 |
completed | March 1, 2026, 8:50 p.m. |
Created at: March 1, 2026, 7:37 p.m.