Triple
T6974971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzania–Zambia Railway |
E161693
|
entity |
| Predicate | avoidsDependenceOn |
P17548
|
FINISHED |
| Object | Rhodesian rail routes |
—
|
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: Rhodesian rail routes | Statement: [Tanzania–Zambia Railway, avoidsDependenceOn, Rhodesian rail routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avoidsDependenceOn Context triple: [Tanzania–Zambia Railway, avoidsDependenceOn, Rhodesian rail routes]
-
A.
doesNotDependOn
Indicates that one entity’s state, behavior, or outcome is completely independent of, and not influenced or determined by, another entity.
-
B.
independenceFrom
Indicates that one entity is not controlled, governed, or significantly influenced by another entity.
-
C.
designedToAvoid
chosen
Indicates that something was intentionally created or configured in a way that prevents or minimizes a particular outcome, condition, or interaction.
-
D.
doesNotUse
Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
-
E.
hasDependency
Indicates that one entity relies on or requires another entity in order to function, exist, or be fulfilled.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db3bda908190a10a91dc8d043ef1 |
completed | March 27, 2026, 7:32 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.