Triple
T6623373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geary Street |
E149730
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Downtown |
E475029
|
NE 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: Downtown | Statement: [Geary Street, hasDistrict, Downtown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downtown Context triple: [Geary Street, hasDistrict, Downtown]
-
A.
Downtown
Downtown is an American television series featuring Mariska Hargitay in a leading role.
-
B.
Downtown
chosen
Downtown is the central business and commercial district of Washington, D.C., known for its offices, shops, restaurants, and proximity to major landmarks.
-
C.
Downtown
"Downtown" is a funk- and hip hop-influenced single by Macklemore & Ryan Lewis, known for its nostalgic homage to old-school rap and mopeds.
-
D.
City Center
City Center is a historic performing arts venue in Midtown Manhattan, best known for its dance, theater, and music programming.
-
E.
Downtown Reach
Downtown Reach is the central, urban section of the San Antonio River Walk known for its dense concentration of restaurants, shops, hotels, and cultural attractions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af7decb08190a7b1ddb95e534a6a |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e44b251481909dca5ff82e1dbf0f |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:58 p.m.