Triple
T903265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asha Hagi Elmi |
E19490
|
entity |
| Predicate | notableOccupationContext |
P20195
|
FINISHED |
| Object | post-civil war Somalia |
—
|
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: post-civil war Somalia | Statement: [Asha Hagi Elmi, notableOccupationContext, post-civil war Somalia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOccupationContext Context triple: [Asha Hagi Elmi, notableOccupationContext, post-civil war Somalia]
-
A.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
C.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
D.
notablePersonnel
Indicates that the subject has associated individuals who are particularly important, distinguished, or prominent in relation to it.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad56f4c08190a7a5091ff0eb3209 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab60fea8819098ce3269181897d1 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.