Triple
T37889199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ekwefi |
E945078
|
entity |
| Predicate | childMortalityExperience |
P76185
|
FINISHED |
| Object | lost many children in infancy |
—
|
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: lost many children in infancy | Statement: [Ekwefi, childMortalityExperience, lost many children in infancy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childMortalityExperience Context triple: [Ekwefi, childMortalityExperience, lost many children in infancy]
-
A.
childDeaths
chosen
Indicates that one or more children of the referenced entity have died.
-
B.
childDiedIn
Indicates that a child died within or as part of the specified event, situation, or context.
-
C.
causeOfDaughterDeaths
Indicates a relationship where an entity is the cause or reason for the deaths of one or more daughters.
-
D.
diedInInfancy
Indicates that an individual died during infancy, before reaching early childhood.
-
E.
numberOfChildrenSurvivors
Indicates the count of children who survived a particular event, condition, or situation.
- 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.