Triple
T8451097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Said |
E199798
|
entity |
| Predicate | portraysTopic |
P12980
|
FINISHED |
| Object | sexual harassment in the workplace |
—
|
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: sexual harassment in the workplace | Statement: [She Said, portraysTopic, sexual harassment in the workplace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysTopic Context triple: [She Said, portraysTopic, sexual harassment in the workplace]
-
A.
portraysGroup
Indicates that one entity depicts, represents, or visually illustrates a group of entities as its subject.
-
B.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
C.
primaryTopicOf
chosen
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
E.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44815488190a912d63512e19af0 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.