Triple
T8521022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnus |
E201692
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Fat Agnus |
E201692
|
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: Fat Agnus | Statement: [Agnus, hasVariant, Fat Agnus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fat Agnus Context triple: [Agnus, hasVariant, Fat Agnus]
-
A.
Fatlip
Fatlip is an American rapper best known as a former member of the influential alternative hip hop group The Pharcyde.
-
B.
Agnus
chosen
Agnus is the custom chip in early Commodore Amiga computers responsible for managing graphics, memory access, and DMA operations within the system’s chipset.
-
C.
Meatu
Meatu is a rural district and administrative settlement in northern Tanzania’s Simiyu Region, known for its agriculture and livestock-keeping communities.
-
D.
Ficulle
Ficulle is a small historic hill town in central Italy’s Umbria region, known for its medieval architecture and scenic countryside.
-
E.
Scallabis
Scallabis was the ancient Roman name for the city now known as Santarém in central Portugal, an important settlement in the Roman province of Lusitania.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e76dcd08190866fde75cd0ac389 |
completed | April 2, 2026, 11:09 a.m. |
Created at: March 30, 2026, 6:16 p.m.