Triple
T13589928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën half-track vehicles |
E324666
|
entity |
| Predicate | notableExpeditionRoute |
P16292
|
FINISHED |
| Object | Africa crossing |
—
|
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: Africa crossing | Statement: [Citroën half-track vehicles, notableExpeditionRoute, Africa crossing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableExpeditionRoute Context triple: [Citroën half-track vehicles, notableExpeditionRoute, Africa crossing]
-
A.
notableExpeditionLocation
Indicates that a location is a significant or primary place associated with a particular expedition.
-
B.
notableRouteFeature
Indicates that a route is associated with a distinctive or significant feature, such as a landmark, characteristic terrain, or other notable aspect along its path.
-
C.
notableRouteType
Indicates that a route is particularly significant or well-known for a specific type or category (e.g., scenic, historic, commercial).
-
D.
hasNotableExpedition
chosen
Indicates that an entity is associated with a significant or noteworthy expedition, journey, or exploratory mission.
-
E.
notableHike
Indicates that an entity is recognized as a significant or well-known hiking route or trail.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.