Triple
T19387105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Διόσπολις |
E484962
|
entity |
| Predicate | usedForMultipleCities |
P52148
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Διόσπολις, usedForMultipleCities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForMultipleCities Context triple: [Διόσπολις, usedForMultipleCities, true]
-
A.
usedInCity
Indicates that something is utilized, applied, or operates within the context or boundaries of a particular city.
-
B.
usesMultipleHostCities
chosen
Indicates that an event or activity is held across more than one host city rather than being confined to a single location.
-
C.
coversCity
Indicates that one entity extends over, includes, or geographically encompasses the area of a specified city.
-
D.
hasMajorCityOfUse
Indicates that a particular city is the primary or most significant location where something (e.g., a product, language, service) is predominantly used or applied.
-
E.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b418f148190972b7b46038bc744 |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:36 p.m.