Triple
T16436097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reb Beach |
E399182
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Beach |
E844405
|
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: Beach | Statement: [Reb Beach, familyName, Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beach Context triple: [Reb Beach, familyName, Beach]
-
A.
Beach
Beach is the long-suffering butler in P. G. Wodehouse’s Blandings Castle stories, known for his dignified composure amid the eccentric chaos of the castle’s inhabitants.
-
B.
Beach
chosen
Beach is a common English surname borne by various notable individuals across politics, journalism, and the arts.
-
C.
Beaches
Beaches is a 1988 American drama film starring Bette Midler that follows the lifelong friendship between two very different women.
-
D.
Beaches
Beaches is a 2017 television drama film that reimagines the 1988 movie about the enduring, complex friendship between two very different women over the course of their lives.
-
E.
Sand Beach
Sand Beach is a small, picturesque sandy shoreline on Mount Desert Island in Maine, known for its cold waters, dramatic rocky surroundings, and popularity with visitors to Acadia National Park.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba224988190b7cccc42f35e54de |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0045893c5481909e5ffa9460dc5b3d |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:10 a.m.