Triple
T10645702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcino |
E250827
|
entity |
| Predicate | hasStructureRemains |
P16216
|
FINISHED |
| Object | sections of Roman walls |
—
|
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: sections of Roman walls | Statement: [Barcino, hasStructureRemains, sections of Roman walls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStructureRemains Context triple: [Barcino, hasStructureRemains, sections of Roman walls]
-
A.
hasRemainsOf
chosen
Indicates that one entity physically contains, preserves, or is associated with the leftover physical traces or remnants of another entity.
-
B.
hasHumanStructure
Indicates that one entity possesses or exhibits a structural form or organization characteristic of humans.
-
C.
hasStructureAbove
Indicates that one entity has another entity positioned vertically higher or located on top of it within a structural or spatial arrangement.
-
D.
remainingStructuresUsedFor
Indicates that the remaining structures of an entity are utilized for a specified purpose or function.
-
E.
hasSignificantStructure
Indicates that an entity possesses a structure or internal organization that is notably complex, important, or meaningful in a given context.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe120908190ab91c38d57133739 |
completed | April 8, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:05 p.m.