Triple
T36799827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentine re-mailing program |
E909288
|
entity |
| Predicate | nicknameOfCityInvolved |
P74834
|
FINISHED |
| Object | Sweetheart City |
—
|
NE NERFINISHED |
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: Sweetheart City | Statement: [Valentine re-mailing program, nicknameOfCityInvolved, Sweetheart City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameOfCityInvolved Context triple: [Valentine re-mailing program, nicknameOfCityInvolved, Sweetheart City]
-
A.
nicknameOfCityItGoverns
Indicates that one entity is a nickname used to refer to a city that another entity governs.
-
B.
nicknameOfTown
Indicates that one entity is a nickname or informal name used to refer to a particular town.
-
C.
cityNicknameAssociation
chosen
Indicates an associative relationship where a particular nickname is used to refer to or characterize a specific city.
-
D.
isInCityNicknamed
Indicates that one entity is located in a city that is known by a particular nickname.
-
E.
cityNickname
Indicates that one entity is commonly used as an informal or alternative name for a city.
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:12 p.m.