Triple
T7261904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg, South Carolina |
E159674
|
entity |
| Predicate | eventVictims |
P59760
|
FINISHED |
| Object | Black militiamen |
—
|
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: Black militiamen | Statement: [Hamburg, South Carolina, eventVictims, Black militiamen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventVictims Context triple: [Hamburg, South Carolina, eventVictims, Black militiamen]
-
A.
mainVictims
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
-
B.
hasVictims
chosen
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
-
C.
numberOfVictimsInjured
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
D.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
E.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:57 p.m.