Triple
T10630496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inez Milholland |
E250439
|
entity |
| Predicate | genreOfSpeech |
P29536
|
FINISHED |
| Object | political oratory |
—
|
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: political oratory | Statement: [Inez Milholland, genreOfSpeech, political oratory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfSpeech Context triple: [Inez Milholland, genreOfSpeech, political oratory]
-
A.
speechType
chosen
Indicates the specific category or form of spoken or written communication that an utterance or speech act belongs to (e.g., question, statement, command).
-
B.
genreOfQuotes
Indicates that one entity is the literary, thematic, or stylistic genre to which the other entity’s quotes belong.
-
C.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
D.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
-
E.
speakerType
Indicates the role or category of a participant in a communicative act (e.g., narrator, quoted speaker, system voice) within a given context.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df93a2b88190a0f3a52b8e88f54f |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7fae088190973f70c69738af49 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:01 p.m.