Triple
T13160941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Addis Ababa–Djibouti Railway |
E312722
|
entity |
| Predicate | replacesMode |
P30993
|
FINISHED |
| Object | road transport along Addis Ababa–Djibouti corridor |
—
|
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: road transport along Addis Ababa–Djibouti corridor | Statement: [Addis Ababa–Djibouti Railway, replacesMode, road transport along Addis Ababa–Djibouti corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacesMode Context triple: [Addis Ababa–Djibouti Railway, replacesMode, road transport along Addis Ababa–Djibouti corridor]
-
A.
seeksToReplace
Indicates an intention or effort by one entity to take over the role, function, or position currently held by another entity.
-
B.
replacedWith
Indicates that one entity has been substituted or superseded by another entity, taking over its role, function, or position.
-
C.
replacesInPractice
chosen
Indicates that one entity has effectively taken over the role, function, or use of another entity in real-world application or usage.
-
D.
replacedStandard
Indicates that one standard has been superseded or taken the place of another standard.
-
E.
replacesWord
Indicates that one word is substituted for another word in a given context or expression.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:12 p.m.