Triple
T12532761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piran |
E299609
|
entity |
| Predicate | oldTownCharacter |
P105746
|
FINISHED |
| Object | medieval urban fabric |
—
|
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: medieval urban fabric | Statement: [Piran, oldTownCharacter, medieval urban fabric]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oldTownCharacter Context triple: [Piran, oldTownCharacter, medieval urban fabric]
-
A.
oldTownStatus
Indicates that a place holds the designation or characteristics of being an old or historic town.
-
B.
hasSmallTownCharacter
Indicates that something possesses the qualities or atmosphere typically associated with a small town, such as intimacy, familiarity, and a close-knit community feel.
-
C.
formerCharacter
Indicates that an entity was once a character in a work or series but is no longer an active or current character.
-
D.
touristCharacter
Indicates that an entity has the role, behavior, or qualities characteristic of a tourist in relation to another entity or context.
-
E.
cityQuarterCharacter
Indicates the characteristic qualities or distinctive nature that define a particular city quarter.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d95f5148948190946a575d812b329d |
completed | April 10, 2026, 8:36 p.m. |
Created at: April 8, 2026, 9:57 p.m.