Triple
T7765025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenri |
E176121
|
entity |
| Predicate | hasCitySymbol |
P10919
|
FINISHED |
| Object | Tenri city emblem |
—
|
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: Tenri city emblem | Statement: [Tenri, hasCitySymbol, Tenri city emblem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitySymbol Context triple: [Tenri, hasCitySymbol, Tenri city emblem]
-
A.
citySymbol
chosen
Indicates that one entity serves as the official symbol or emblem representing a particular city.
-
B.
citySymbolOf
Indicates that a particular city serves as an official symbol or emblem representing another entity, such as a region, organization, or concept.
-
C.
cantonSymbol
Indicates that one entity serves as the official symbol or emblem representing a particular canton.
-
D.
flagshipCity
Indicates that a city serves as the primary, most representative, or leading example within a larger group, organization, or context.
-
E.
emblematicFor
Indicates that something serves as a representative symbol or characteristic example of something else.
- 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_69c69962923c8190ac74d28b4f9fe0a0 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7043279748190b30882e9cc6cca54 |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:09 p.m.