Triple
T9064635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Luther King Jr. Avenue SE |
E217213
|
entity |
| Predicate | hasStreetDesignation |
P62637
|
FINISHED |
| Object | Avenue SE |
—
|
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: Avenue SE | Statement: [Martin Luther King Jr. Avenue SE, hasStreetDesignation, Avenue SE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetDesignation Context triple: [Martin Luther King Jr. Avenue SE, hasStreetDesignation, Avenue SE]
-
A.
hasStreetNameElement
chosen
Indicates that an address or location includes a specific street name component as part of its full designation.
-
B.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
C.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
D.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
E.
hasCityDesignatedAs
Indicates that an entity has a specific city formally assigned or designated to it in a particular role or capacity.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc94bb26588190b7d6f2d70819e86f |
completed | April 1, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:11 p.m.