Triple
T22974373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fart and Wiener Jokes |
E571273
|
entity |
| Predicate | spokenWord |
P150458
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fart and Wiener Jokes, spokenWord, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenWord Context triple: [Fart and Wiener Jokes, spokenWord, true]
-
A.
spokenAlong
Indicates that two or more languages are used concurrently or within the same context in a particular place, time, or situation.
-
B.
spokeWords
Indicates that one entity verbally expressed specific words to another entity or audience.
-
C.
spokenOfAs
Indicates that one entity is referred to, characterized, or talked about in a particular way by another entity or within a given context.
-
D.
spokenUntil
Indicates that an act of speaking or verbal communication continues up to a specific time or event and then stops.
-
E.
isSpoken
Indicates that a language or utterance is produced orally by a speaker or used in spoken form within a given context.
- F. None of above. chosen
Provenance (4 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182350b448190a34e5fa0167fd964 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:48 p.m.