Triple
T2106257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Uhud |
E42400
|
entity |
| Predicate | distanceFromMedinaCenterApprox |
P35868
|
FINISHED |
| Object | about 5 kilometers |
—
|
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 5 kilometers | Statement: [Mount Uhud, distanceFromMedinaCenterApprox, about 5 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMedinaCenterApprox Context triple: [Mount Uhud, distanceFromMedinaCenterApprox, about 5 kilometers]
-
A.
distanceFromMecca
Indicates the measured spatial distance between a given location and the city of Mecca.
-
B.
distanceFromMeccaApprox
Indicates an approximate measure of how far something is located from Mecca.
-
C.
distanceFromCairo
Indicates the measured spatial distance between a given entity’s location and the city of Cairo.
-
D.
distanceFromBaghdad
Indicates the spatial distance between a given location or entity and the city of Baghdad.
-
E.
distanceFromMarrakesh
Indicates the spatial distance between a given location and the city of Marrakesh.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbaddeb148190b728bce7a7b041fb |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb9ce3ff08190a9501f8bb821c01c |
completed | March 7, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:43 p.m.