Triple
T25423216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banks |
E637038
|
entity |
| Predicate | hasStreetNamingTheme |
P128235
|
FINISHED |
| Object | botanists |
—
|
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: botanists | Statement: [Banks, hasStreetNamingTheme, botanists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetNamingTheme Context triple: [Banks, hasStreetNamingTheme, botanists]
-
A.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
B.
hasStreetNickname
Indicates that an entity is known by a particular informal or colloquial name used on the street or in everyday speech.
-
C.
streetPatternNamedFor
Indicates that a street pattern or layout is named in honor of, or derived from, a particular entity.
-
D.
hasStreetNameLanguage
Indicates that the language in which a street name is expressed is specified.
-
E.
hasStreetNameOrigin
chosen
Indicates that the origin or source of a street’s name is specified or linked to a particular cause, person, event, or feature.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 21, 2026, 1:57 p.m.