Triple
T32307210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Procuracies |
E825399
|
entity |
| Predicate | hasArcadesAlong |
P24796
|
FINISHED |
| Object | north side of St Mark's Square |
—
|
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: north side of St Mark's Square | Statement: [Old Procuracies, hasArcadesAlong, north side of St Mark's Square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArcadesAlong Context triple: [Old Procuracies, hasArcadesAlong, north side of St Mark's Square]
-
A.
hasArcades
chosen
Indicates that one entity features or contains arcaded structures (a series of arches or covered passageways) associated with another entity.
-
B.
hasSlotMachines
Indicates that an entity contains, offers, or is equipped with one or more slot machines.
-
C.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
D.
notableArcadeGame
Indicates that the subject is an arcade game that is particularly famous, influential, or otherwise noteworthy.
-
E.
arcadeStandard
Indicates that something conforms to, or is defined as, the standard or typical form used in arcade contexts (such as games, machines, or configurations).
- 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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: May 1, 2026, 12:45 a.m.