Triple
T21673940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRRR! |
E534919
|
entity |
| Predicate | notableTrack |
P8087
|
FINISHED |
| Object | Angie |
—
|
NE NERFINISHED |
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: Angie | Statement: [GRRR!, notableTrack, Angie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angie Context triple: [GRRR!, notableTrack, Angie]
-
A.
Angie
Angie is the modern nickname and alias used for the character Angelique Bouchard from the gothic soap opera "Dark Shadows."
-
B.
Angie
Angie is a central character in Caryl Churchill’s play "Top Girls," portrayed as a troubled and vulnerable young girl whose future and identity are shaped by the play’s feminist and social themes.
-
C.
Angie
chosen
"Angie" is a 1973 ballad by The Rolling Stones, renowned for its melancholic melody and emotional lyrics, and considered one of the band's most iconic songs.
-
D.
Angie
"Angie" is an American sitcom from the late 1970s that follows the romantic and family life of a working-class woman who marries into a wealthy family.
-
E.
Angie
Angie is a fictional private investigator featured in Dennis Lehane’s crime novel series alongside her partner Patrick Kenzie.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a0e06688190a75ea29534f5eed3 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 16, 2026, 6:41 p.m.