Triple
T9880310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Mark |
E180783
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Amber Mark |
E180783
|
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: Amber Mark | Statement: [Amber Mark, name, Amber Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amber Mark Context triple: [Amber Mark, name, Amber Mark]
-
A.
Amber Mark
chosen
Amber Mark is an American singer, songwriter, and producer known for her soulful blend of R&B, pop, and global influences.
-
B.
Amber Seyer
Amber Seyer is an American model and former Miss Missouri Teen USA who is married to former Major League Baseball pitcher Barry Zito.
-
C.
Amber Mariens
Amber Mariens is a fashion-obsessed, snobbish high school student who serves as a comic foil in the television adaptation of "Clueless."
-
D.
Honeysuckle Weeks
Honeysuckle Weeks is a British actress best known for playing Samantha Stewart in the television detective drama series "Foyle's War."
-
E.
Jean Grae
Jean Grae is an American underground hip-hop MC known for her intricate lyricism, sharp wordplay, and influential role in New York’s indie rap scene.
- 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_69ca828082cc8190a40f8d299caa6545 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4146fe881908f9fc553dfca31e1 |
completed | April 2, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e48665e88190ab8a4a30b1df8ebe |
completed | April 5, 2026, 4:26 a.m. |
Created at: March 30, 2026, 8:38 p.m.