Triple
T12933969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Speicher massacre |
E309453
|
entity |
| Predicate | hasPrimaryVictimGroup |
P82701
|
FINISHED |
| Object | Shia Iraqi Air Force cadets |
—
|
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: Shia Iraqi Air Force cadets | Statement: [Camp Speicher massacre, hasPrimaryVictimGroup, Shia Iraqi Air Force cadets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryVictimGroup Context triple: [Camp Speicher massacre, hasPrimaryVictimGroup, Shia Iraqi Air Force cadets]
-
A.
hasMainVictim
chosen
Indicates that an event, action, or harmful situation primarily targets or affects a specific victim as its main subject.
-
B.
hasVictimCount
Indicates the number of victims associated with a particular event, action, or entity.
-
C.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
D.
hasVictims
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
-
E.
hasVictimNationalities
Indicates that an event, incident, or action involved victims belonging to one or more specified nationalities.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.