Triple
T4852412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamar |
E108446
|
entity |
| Predicate | reactionAfterAssault |
P48782
|
FINISHED |
| Object | tore her ornate robe |
—
|
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: tore her ornate robe | Statement: [Tamar, reactionAfterAssault, tore her ornate robe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reactionAfterAssault Context triple: [Tamar, reactionAfterAssault, tore her ornate robe]
-
A.
assaultedBy
Indicates that an entity has been attacked or subjected to violent physical aggression by another entity.
-
B.
trauma
Indicates that an entity has experienced a deeply distressing or harmful event or series of events that cause lasting psychological or emotional impact.
-
C.
aftermathOf
chosen
Indicates that one event, state, or condition occurs as a consequence or result following another event.
-
D.
usedViolenceAgainst
Indicates that one entity intentionally inflicted physical force or harm upon another entity.
-
E.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.