Triple
T16717386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moody Blue |
E406258
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Let Me Be There (live) |
E368832
|
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: Let Me Be There (live) | Statement: [Moody Blue, hasPart, Let Me Be There (live)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Let Me Be There (live) Context triple: [Moody Blue, hasPart, Let Me Be There (live)]
-
A.
Let Me Be There
chosen
"Let Me Be There" is a 1973 country-pop song by Olivia Newton-John that became one of her early breakthrough hits and earned her a Grammy Award.
-
B.
I’ll Be There
"I’ll Be There" is a soulful track performed by Cissy Houston, featured on her self-titled album.
-
C.
I’ll Be There
"I’ll Be There" is a soulful pop song by British singer Jess Glynne, known for its uplifting lyrics and powerful vocal performance.
-
D.
I'll Be There
"I'll Be There" is a soulful 1970 ballad by The Jackson 5 that became one of their signature hits and a defining Motown classic.
-
E.
I'll Be There
"I'll Be There" is a novel by American author and screenwriter Iris Rainer Dart, best known for writing the bestseller "Beaches."
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38656b66081909f2c2a8971c45aee |
completed | April 18, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d3da12881909296926edde5b723 |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:20 a.m.