Triple
T599633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan |
E11464
|
entity |
| Predicate | isGlobalCityFor |
P16839
|
FINISHED |
| Object | fashion |
—
|
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: fashion | Statement: [Milan, isGlobalCityFor, fashion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGlobalCityFor Context triple: [Milan, isGlobalCityFor, fashion]
-
A.
isGlobalCityRank
Indicates the relative position or ranking of a city within a global hierarchy of cities based on specified criteria.
-
B.
isMajorCityIn
Indicates that a city is a primary or significant urban center located within a specified larger region or country.
-
C.
isMegacity
Indicates that a city has an extremely large population and urban area, typically qualifying it as a major global metropolitan center.
-
D.
hasFamousCity
Indicates that an entity possesses or is associated with a city that is widely recognized or renowned.
-
E.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49dc4f7d08190990f70b9b3af6ce5 |
completed | March 1, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69a49cf59cd0819084e67981cb371e25 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49dc0e6a08190b81d82a6f2571c41 |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:35 p.m.