Triple
T6467099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1998 United States embassy bombings |
E142257
|
entity |
| Predicate | notableVictimCountKenya |
P63692
|
FINISHED |
| Object | over 200 killed in Nairobi |
—
|
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: over 200 killed in Nairobi | Statement: [1998 United States embassy bombings, notableVictimCountKenya, over 200 killed in Nairobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVictimCountKenya Context triple: [1998 United States embassy bombings, notableVictimCountKenya, over 200 killed in Nairobi]
-
A.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
B.
notableVictims
Indicates that the object is a person or group who is especially well-known or significant as a victim of the subject.
-
C.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
D.
mainVictims
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
-
E.
childrenKilledBy
Indicates that the children of a given entity were killed by another specified entity or agent.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a12ccf481908f71f888cd744b64 |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:49 p.m.