Triple
T4744586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malmedy massacre |
E105328
|
entity |
| Predicate | victimStatus |
P58515
|
FINISHED |
| Object | disarmed combatants |
—
|
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: disarmed combatants | Statement: [Malmedy massacre, victimStatus, disarmed combatants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimStatus Context triple: [Malmedy massacre, victimStatus, disarmed combatants]
-
A.
victimParticipation
Indicates that the victim took part in, contributed to, or was otherwise involved in the event or action described.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
victimAge
Indicates the age of the person who is the victim in the described event or situation.
-
D.
victimTitle
Indicates that one entity holds a title, role, or designation specifically in the capacity of being a victim in relation to another entity or event.
-
E.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
- F. None of above. chosen
Provenance (4 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64aa72c0819082ede0f531d75e65 |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd637e19e081909e415544106c7835 |
completed | March 20, 2026, 3:10 p.m. |
Created at: March 20, 2026, 1:19 p.m.