Triple
T31683565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hälfte des Lebens |
E808596
|
entity |
| Predicate | secondStanzaMood |
P48412
|
FINISHED |
| Object | bleak desolation |
—
|
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: bleak desolation | Statement: [Hälfte des Lebens, secondStanzaMood, bleak desolation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondStanzaMood Context triple: [Hälfte des Lebens, secondStanzaMood, bleak desolation]
-
A.
secondaryMood
Indicates a secondary or accompanying emotional state that exists alongside a primary mood in a given context.
-
B.
verse2
chosen
Indicates that one entity is the second verse or stanza associated with another entity, typically within a structured text like a song, poem, or scripture.
-
C.
secondaryEmotion
Indicates that one emotion arises as a secondary, derivative, or reactive feeling in response to a primary emotion.
-
D.
secondSyllable
Indicates that the second syllable of one linguistic unit corresponds to, matches, or is identified as a particular syllable or sound in relation to another entity.
-
E.
secondWord
Indicates that one entity is the second word in sequence immediately following the first entity in a text or utterance.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: April 30, 2026, 11:05 p.m.