Triple
T8579415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bliss |
E203129
|
entity |
| Predicate | appearsAlongside |
P25756
|
FINISHED |
| Object | Dom |
unclear NED1
|
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: Dom | Statement: [Bliss, appearsAlongside, Dom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dom Context triple: [Bliss, appearsAlongside, Dom]
-
A.
Dom
Dom is one of the highest and most prominent mountains in the Swiss Alps, renowned for its imposing pyramid shape and challenging climbing routes.
-
B.
Dom
Dom is a Portuguese honorific title traditionally used for nobility, royalty, and certain high-ranking religious figures.
-
C.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
D.
Don
Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
-
E.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea9a0708819084cb8b8d84017864 |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea89550f481908a7ed45303b71731 |
completed | April 2, 2026, 5:34 p.m. |
Created at: March 30, 2026, 6:22 p.m.