Triple
T8737455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corinium Dobunnorum |
E207420
|
entity |
| Predicate | approximateRankBySize |
P1174
|
FINISHED |
| Object | second largest town in Roman Britain |
—
|
LITERAL 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: second largest town in Roman Britain | Statement: [Corinium Dobunnorum, approximateRankBySize, second largest town in Roman Britain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateRankBySize Context triple: [Corinium Dobunnorum, approximateRankBySize, second largest town in Roman Britain]
-
A.
rankBySize
chosen
Indicates that entities are ordered or compared based on their size.
-
B.
rankBySizeInWorld
Indicates that entities are ordered according to their relative size within the context of the entire world.
-
C.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
D.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
E.
rankEquivalent
Indicates that two entities hold the same rank or hierarchical level within a given ordering or classification system.
- F. None of above.
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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d45c96081909aa8509064ff3a04 |
completed | March 31, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:38 p.m.