Triple
T9144930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ancient State of Sui |
E219427
|
entity |
| Predicate | hasToponymicLegacy |
P53681
|
FINISHED |
| Object | place names in Suizhou area |
—
|
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: place names in Suizhou area | Statement: [ancient State of Sui, hasToponymicLegacy, place names in Suizhou area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToponymicLegacy Context triple: [ancient State of Sui, hasToponymicLegacy, place names in Suizhou area]
-
A.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
B.
hasToponymicUse
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
C.
hasToponymicDerivatives
chosen
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
D.
hasToponymicForm
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
E.
hasNotableToponym
Indicates that an entity is associated with a place name that is particularly notable, distinctive, or significant.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca9166d308190a742ae68371439ee |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.