Triple
T14227090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipal Tobacco Warehouse |
E352648
|
entity |
| Predicate | significanceForCity |
P18147
|
FINISHED |
| Object | symbol of Kavala commercial prosperity |
—
|
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: symbol of Kavala commercial prosperity | Statement: [Municipal Tobacco Warehouse, significanceForCity, symbol of Kavala commercial prosperity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significanceForCity Context triple: [Municipal Tobacco Warehouse, significanceForCity, symbol of Kavala commercial prosperity]
-
A.
notableImpactCity
Indicates that an entity has had a significant or widely recognized impact on a particular city.
-
B.
notableInCity
chosen
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
-
C.
hasCivicSignificance
Indicates that something holds importance, relevance, or impact within a civic or public context, such as community life, governance, or public affairs.
-
D.
cityOfInfluence
Indicates the city that significantly shapes, impacts, or exerts influence over a given entity.
-
E.
hasRegionalSignificance
Indicates that something holds particular importance, influence, or relevance within a specific geographic region.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622a48508190bbfedb762bd1674d |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:07 a.m.