Triple
T8007752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Brown |
E186405
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Loyal |
E334996
|
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: Loyal | Statement: [Chris Brown, notableWork, Loyal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loyal Context triple: [Chris Brown, notableWork, Loyal]
-
A.
Loyal
chosen
"Loyal" is a popular R&B/hip-hop song best known for its catchy hook and multiple high-profile guest features, including Ty Dolla Sign.
-
B.
Forever Loyal
Forever Loyal is the English motto expressing the unwavering dedication and fidelity of the Republic of China Marine Corps.
-
C.
Steadfast and Loyal
Steadfast and Loyal is the official motto of the U.S. Army’s 4th Infantry Division, reflecting its enduring commitment to duty, reliability, and perseverance in combat.
-
D.
Loyalties
Loyalties is a 1922 play by John Galsworthy that explores themes of anti-Semitism, class prejudice, and moral responsibility within upper-class English society.
-
E.
"Loyalty"
"Loyalty" is a hip-hop single by Birdman that showcases his signature Southern rap style and themes of allegiance and street credibility.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6e1c9081909018bcebb18906f6 |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc5697ac9081909fe7ca06d0c3ef38 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:18 p.m.