Triple
T16884701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Algren |
E421508
|
entity |
| Predicate | traumaFrom |
P41242
|
FINISHED |
| Object | massacre of Native Americans |
—
|
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: massacre of Native Americans | Statement: [Nathan Algren, traumaFrom, massacre of Native Americans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traumaFrom Context triple: [Nathan Algren, traumaFrom, massacre of Native Americans]
-
A.
trauma
chosen
Indicates that an entity has experienced a deeply distressing or harmful event or series of events that cause lasting psychological or emotional impact.
-
B.
traumaLevel
Indicates the degree or severity of trauma experienced or present in relation to an entity or event.
-
C.
traumaTheme
Indicates that the relationship or context involves themes of trauma, such as psychological injury, distressing experiences, or their emotional and narrative impact.
-
D.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
E.
actedDespiteWounds
Indicates that an entity performed an action or fulfilled a role even though it was wounded or injured at the time.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc00cf8819088a08ddb00cd3c96 |
completed | April 18, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.