Triple
T36616012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bié Province |
E903604
|
entity |
| Predicate | usedToBeImportantFor |
P2417
|
FINISHED |
| Object | rail transport in Angola |
—
|
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: rail transport in Angola | Statement: [Bié Province, usedToBeImportantFor, rail transport in Angola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToBeImportantFor Context triple: [Bié Province, usedToBeImportantFor, rail transport in Angola]
-
A.
usedToBe
Indicates that something held a particular state, role, or property in the past but no longer does in the present.
-
B.
historicallyUsedFor
chosen
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
-
C.
isImportantFor
Indicates that something holds significant value, relevance, or necessity in relation to something else.
-
D.
wasPopularBefore
Indicates that one entity enjoyed a higher level of popularity than another during an earlier time period.
-
E.
usedLessIn
Indicates that one entity is used with a lower frequency or intensity compared to another entity.
- 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.