Triple
T24138466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saro people |
E598154
|
entity |
| Predicate | legalStatusInSierraLeone |
P154985
|
FINISHED |
| Object | Liberated Africans |
—
|
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: Liberated Africans | Statement: [Saro people, legalStatusInSierraLeone, Liberated Africans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusInSierraLeone Context triple: [Saro people, legalStatusInSierraLeone, Liberated Africans]
-
A.
hasLegalStatusInSudan
Indicates that an entity holds a recognized legal status or standing within the jurisdiction of Sudan.
-
B.
representedInSierraLeoneBy
Indicates that one entity serves as the official representative or agent of another entity specifically within the jurisdiction of Sierra Leone.
-
C.
legalStatusInElSalvador
Indicates the legal status or standing that an entity has under the laws and regulations of El Salvador.
-
D.
legalStatusInMostCountries
Indicates the typical legal classification or treatment of something across the majority of countries.
-
E.
legalStatusInIraq
Indicates the legal status or standing that an entity holds under the laws and regulations of Iraq.
- F. None of above. chosen
Provenance (4 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_69e288c92e448190ac57034fa0c863ce |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1df7e3c20819099ff289789829d7e |
completed | April 29, 2026, 10:37 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 11:27 p.m.