Triple
T12005717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voodoo Lounge |
E285773
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Love Is Strong |
E285753
|
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: Love Is Strong | Statement: [Voodoo Lounge, hasTrack, Love Is Strong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Is Strong Context triple: [Voodoo Lounge, hasTrack, Love Is Strong]
-
A.
Love Is Strong
chosen
"Love Is Strong" is a 1994 rock song by The Rolling Stones, known for its gritty blues-influenced sound and award-winning music video.
-
B.
Love Is
"Love Is" is an R&B studio album by American singer and American Idol winner Ruben Studdard.
-
C.
Love Is On
"Love Is On" is a marketing slogan used by Revlon to promote its beauty and cosmetics products with a focus on passion, romance, and emotional connection.
-
D.
Love Is All
Love Is All is a Dutch romantic comedy film known for its ensemble cast and interwoven love stories set in Amsterdam.
-
E.
Our Love
"Our Love" is a popular R&B/soul song by American singer Natalie Cole, known for showcasing her rich vocals and romantic style in the late 1970s.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c5cfc08190821e4b2940c51416 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b0574d48190b336a6b9a4ada2a8 |
completed | May 1, 2026, 11:14 a.m. |
Created at: April 8, 2026, 9:46 p.m.