Triple
T25131184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Sinai attacks (October 2014) |
E629525
|
entity |
| Predicate | casualtiesSecurityForcesKilled |
P94247
|
FINISHED |
| Object | dozens |
—
|
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: dozens | Statement: [2014 Sinai attacks (October 2014), casualtiesSecurityForcesKilled, dozens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesSecurityForcesKilled Context triple: [2014 Sinai attacks (October 2014), casualtiesSecurityForcesKilled, dozens]
-
A.
militaryDeaths
Indicates the number of individuals who died while serving in a military capacity, typically during armed conflict or related operations.
-
B.
militaryUnitInvolvedInDeath
Indicates that a specific military unit participated in, contributed to, or was otherwise involved in causing a particular death.
-
C.
governmentCasualties
chosen
Indicates that members of a government (such as officials, employees, or security forces) were killed, injured, or otherwise became casualties in an event or conflict.
-
D.
casualtiesCiviliansKilled
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
E.
casualtiesUnionKilled
Indicates that the number of casualties consists of individuals who were killed and were members of a union.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 6:28 a.m.