Triple
T15786944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Somali famine of 1992 |
E382759
|
entity |
| Predicate | estimatedDeathsUpperBound |
P700
|
FINISHED |
| Object | 300000 |
—
|
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: 300000 | Statement: [Somali famine of 1992, estimatedDeathsUpperBound, 300000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedDeathsUpperBound Context triple: [Somali famine of 1992, estimatedDeathsUpperBound, 300000]
-
A.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
B.
estimatedVictimsUpperBound
Indicates the maximum estimated number of victims associated with an event, incident, or situation.
-
C.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
D.
estimatedVictimsLowerBound
Indicates the minimum estimated number of victims associated with an event, entity, or incident.
-
E.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0540380448190a025338f0e62e6d1 |
completed | April 16, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.