Triple
T13855209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady A |
E333045
|
entity |
| Predicate | notableSingle |
P3283
|
FINISHED |
| Object | Downtown |
E1066847
|
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: [Lady A, notableSingle, Downtown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downtown Context triple: [Lady A, notableSingle, Downtown]
-
A.
Downtown
Downtown is an American television series featuring Mariska Hargitay in a leading role.
-
B.
Downtown
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 1964 pop song by Petula Clark that became an international hit and one of her signature recordings.
-
D.
Downtown
Downtown refers to the central urban area of a city, typically its main commercial and business district.
-
E.
Downtown
chosen
"Downtown" is a 2010 country-pop song by Lady A (formerly Lady Antebellum), known for its upbeat tempo and playful lyrics about escaping routine for a night out in the city.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02db9c9c81909bb2d2fbfb7394b1 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c70a59e8819090b750699993a107 |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:14 p.m.