Triple
T11415985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamm-Bamm Rubble |
E270492
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | Bedrock |
E270493
|
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: Bedrock | Statement: [Bamm-Bamm Rubble, setting, Bedrock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bedrock Context triple: [Bamm-Bamm Rubble, setting, Bedrock]
-
A.
Bedrock
chosen
Bedrock is the prehistoric, stone-age town that serves as the primary setting of the animated television series "The Flintstones."
-
B.
Thaton
Thaton is an ancient city in southern Myanmar historically significant as a major center of the Mon kingdom and Theravada Buddhism in the region.
-
C.
Edenborn
Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
-
D.
Marble City
Marble City is a nickname for Sylacauga, Alabama, reflecting its long history of marble quarrying and production.
-
E.
Marble City
Marble City is the nickname of Kilkenny, an Irish city famed for its distinctive black limestone and historic architecture.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801ae47d0819098123505309c4a68 |
completed | April 9, 2026, 7:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e8d6392881908fd33d340f3334e7 |
completed | April 20, 2026, 8:50 a.m. |
Created at: April 8, 2026, 9:34 p.m.