Triple
T10478554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marathon des Sables |
E247108
|
entity |
| Predicate | checkpoints |
P30109
|
FINISHED |
| Object | water distribution points |
—
|
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: water distribution points | Statement: [Marathon des Sables, checkpoints, water distribution points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: checkpoints Context triple: [Marathon des Sables, checkpoints, water distribution points]
-
A.
hadCheckpoint
Indicates that an entity passed through, reached, or was associated with a specific checkpoint at some point in time.
-
B.
wasCheckpointName
Indicates that an entity previously had a specific checkpoint name assigned to it.
-
C.
crossesAtMilepost
Indicates that one entity crosses or intersects another at a specific milepost location.
-
D.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
E.
hasCheckpoint
chosen
Indicates that an entity includes, contains, or is associated with one or more intermediate control or verification points within its structure, process, or path.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095a25708190bf34e3ca1491e003 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:21 p.m.