Triple
T8023282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Offset |
E186789
|
entity |
| Predicate | notableSingle |
P3283
|
FINISHED |
| Object | Jealousy |
E189478
|
NE 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: Jealousy | Statement: [Offset, notableSingle, Jealousy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jealousy Context triple: [Offset, notableSingle, Jealousy]
-
A.
Jealousy
chosen
"Jealousy" is a melancholic synth-pop song by the Pet Shop Boys, known for its orchestral arrangement and themes of emotional insecurity and romantic suspicion.
-
B.
Resentment
"Resentment" is an R&B ballad best known for Beyoncé's emotionally charged rendition about betrayal and heartbreak.
-
C.
Lust
Lust is a controversial and stylistically experimental novel by Austrian Nobel laureate Elfriede Jelinek that offers a stark, feminist critique of sexual violence and patriarchal power.
-
D.
Passion
Passion is a 1994 Stephen Sondheim musical known for its intense exploration of obsessive love and emotional vulnerability.
-
E.
Anger
Anger is a municipality in the Bavarian Alps of southeastern Germany, known for its scenic landscapes and traditional rural character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8fb6788190a16413051ec26988 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56cdce588190abba45c24dc7a5e7 |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:21 p.m.