Triple
T23396809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Trees and PhDs |
E559381
|
entity |
| Predicate | cityCharacterizedBy |
P58917
|
FINISHED |
| Object | leafy, tree-lined streets |
—
|
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: leafy, tree-lined streets | Statement: [City of Trees and PhDs, cityCharacterizedBy, leafy, tree-lined streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityCharacterizedBy Context triple: [City of Trees and PhDs, cityCharacterizedBy, leafy, tree-lined streets]
-
A.
cityQuarterCharacter
Indicates the characteristic qualities or distinctive nature that define a particular city quarter.
-
B.
cityDescribedAs
chosen
Indicates that a city is characterized or portrayed using a particular description, label, or set of attributes.
-
C.
cityDepicted
Indicates that a work (such as an image, artwork, or document) visually or representationally depicts a particular city.
-
D.
hasPortCityCharacteristicsOf
Indicates that one entity possesses or exhibits the defining features, functions, or qualities typically associated with a port city of another entity.
-
E.
notableCityIdentity
Indicates that an entity is recognized or distinguished specifically in the context or identity of a particular 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4dc48008190bdcf92f8d9a5232d |
completed | April 29, 2026, 6:27 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:37 p.m.