Triple
T25621678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teresa Harris |
E642313
|
entity |
| Predicate | workplaceHarassmentType |
P79212
|
FINISHED |
| Object | hostile work environment |
—
|
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: hostile work environment | Statement: [Teresa Harris, workplaceHarassmentType, hostile work environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workplaceHarassmentType Context triple: [Teresa Harris, workplaceHarassmentType, hostile work environment]
-
A.
typeOfAbuse
Indicates the specific kind or category of abusive behavior that one entity inflicts on another.
-
B.
allegedHarassmentContext
Indicates the situational or circumstantial context in which an alleged act of harassment is claimed to have occurred.
-
C.
typeOfViolenceAddressed
Indicates the specific form or category of violence that is being targeted, dealt with, or addressed in a given context.
-
D.
typeOfVictimization
chosen
Indicates the specific kind or category of harmful act, abuse, or exploitation experienced by a victim.
-
E.
situationType
Indicates the general kind or category of situation, event, or circumstance that a given instance represents.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 21, 2026, 5:05 p.m.