Triple
T28987636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Free State |
E734731
|
entity |
| Predicate | hasTownKnownFor |
P2813
|
FINISHED |
| Object | Ficksburg cherry festival |
—
|
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: Ficksburg cherry festival | Statement: [Eastern Free State, hasTownKnownFor, Ficksburg cherry festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTownKnownFor Context triple: [Eastern Free State, hasTownKnownFor, Ficksburg cherry festival]
-
A.
isInTownKnownFor
Indicates that one entity is located in a town that is notable or distinguished for the other entity.
-
B.
hasFamousCity
chosen
Indicates that an entity possesses or is associated with a city that is widely recognized or renowned.
-
C.
traditionallyKnownFor
Indicates that something is widely and historically recognized or reputed for a particular characteristic, activity, product, or role.
-
D.
isLocatedInDistrictKnownFor
Indicates that an entity is situated within a district that is notably recognized for a particular characteristic, feature, or reputation.
-
E.
hasLandmarkCity
Indicates that a particular landmark is located within or associated with a specific 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 28, 2026, 9:15 a.m.