Triple
T15909317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Franzese |
E385803
|
entity |
| Predicate | spokePubliclyAbout |
P68313
|
FINISHED |
| Object | body positivity |
—
|
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: body positivity | Statement: [Daniel Franzese, spokePubliclyAbout, body positivity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokePubliclyAbout Context triple: [Daniel Franzese, spokePubliclyAbout, body positivity]
-
A.
spokenOn
Indicates that an utterance or speech act occurred at or during a specific time or date.
-
B.
spokeAt
Indicates that a person delivered a talk, speech, or presentation at a particular event or location.
-
C.
hasSpokenAbout
Indicates that one entity has verbally expressed, discussed, or mentioned another entity or topic.
-
D.
publicStatements
chosen
Indicates that one entity makes official or public verbal or written declarations about another entity or topic.
-
E.
spokenOfAs
Indicates that one entity is referred to, characterized, or talked about in a particular way by another entity or 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.