Triple
T13004643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cher Horowitz |
E322252
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Dionne Davenport |
E327198
|
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: Dionne Davenport | Statement: [Cher Horowitz, closeFriend, Dionne Davenport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dionne Davenport Context triple: [Cher Horowitz, closeFriend, Dionne Davenport]
-
A.
Dionne Davenport
chosen
Dionne Davenport is a stylish, sharp-tongued high school student and Cher Horowitz’s best friend in the 1995 teen comedy film "Clueless."
-
B.
Dionne Harris
Dionne Harris is known as the spouse of Australian actor and musician Noah Taylor.
-
C.
Dionne
Dionne is a given name most famously associated with American singer Dionne Warwick.
-
D.
Diane Chambers
Diane Chambers is an intelligent, sophisticated, and often pretentious waitress and love interest of Sam Malone on the classic American sitcom "Cheers."
-
E.
Donell Jones
Donell Jones is an American R&B singer, songwriter, and producer best known for smooth, soulful hits like "Where I Wanna Be" and "U Know What's Up."
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9a2a448190968833354280e474 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbc5c9a88190b70bda472bf3b062 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:47 p.m.