Triple
T22810407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddy |
E564656
|
entity |
| Predicate | friendOf |
P8712
|
FINISHED |
| Object | Chloe |
—
|
NE NERFINISHED |
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: Chloe | Statement: [Buddy, friendOf, Chloe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chloe Context triple: [Buddy, friendOf, Chloe]
-
A.
Chloe
Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
-
B.
Chloe
Chloe is a sarcastic, food-loving, overweight gray tabby cat from the animated film "The Secret Life of Pets."
-
C.
Chloe
Chloe is a 2009 psychological thriller film directed by Atom Egoyan, known for its themes of infidelity and obsession and starring Amanda Seyfried, Julianne Moore, and Liam Neeson.
-
D.
Chloe
Chloe is a woman mentioned in the New Testament (1 Corinthians) as a member of the early Christian community in Corinth whose household reported divisions in the church to the Apostle Paul.
-
E.
Chloe
Chloe is the pampered white Chihuahua who serves as the central protagonist in the family comedy film "Beverly Hills Chihuahua."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d60186881908f6cb609c536dc91 |
completed | April 29, 2026, 3:39 a.m. |
Created at: April 17, 2026, 3:32 p.m.