Triple
T3828098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadrian's Arch (Athens) |
E88740
|
entity |
| Predicate | symbolicallySeparated |
P52218
|
FINISHED |
| Object | old Greek city of Athens |
—
|
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: old Greek city of Athens | Statement: [Hadrian's Arch (Athens), symbolicallySeparated, old Greek city of Athens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolicallySeparated Context triple: [Hadrian's Arch (Athens), symbolicallySeparated, old Greek city of Athens]
-
A.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
B.
separatedInto
Indicates that something has been divided or split into distinct parts, groups, or components.
-
C.
separatesBy
Indicates that one entity divides, partitions, or creates a boundary between two or more other entities.
-
D.
separationMethod
Indicates the technique or process used to separate one substance, component, or entity from another.
-
E.
separatesState
Indicates that one entity serves as a dividing boundary or barrier between two distinct states or regions.
- F. None of above. chosen
Provenance (4 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8459f881908a2c91bb07e381ef |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb828fb08190901d51edbe8bd304 |
completed | March 9, 2026, 3:47 p.m. |
Created at: March 9, 2026, 3:17 p.m.