Triple
T4895064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloody Sunday |
E109656
|
entity |
| Predicate | hasVictimType |
P16808
|
FINISHED |
| Object | civilian protesters |
—
|
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: civilian protesters | Statement: [Bloody Sunday, hasVictimType, civilian protesters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVictimType Context triple: [Bloody Sunday, hasVictimType, civilian protesters]
-
A.
hasVictimCount
Indicates the number of victims associated with a particular event, action, or entity.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
hasVictimNationalities
Indicates that an event, incident, or action involved victims belonging to one or more specified nationalities.
-
D.
hasMannerOfDeathOfVictim
Indicates the specific way or circumstances in which the victim died in relation to the event or action being described.
-
E.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.