Triple
T16323693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WDSY-FM |
E396360
|
entity |
| Predicate | sisterStation |
P15137
|
FINISHED |
| Object | WAMO |
E396361
|
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: WAMO | Statement: [WDSY-FM, sisterStation, WAMO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WAMO Context triple: [WDSY-FM, sisterStation, WAMO]
-
A.
WAMO
chosen
WAMO is a Pittsburgh-area radio station historically known for its urban contemporary and hip-hop programming serving the region’s Black community.
-
B.
WAM
WAM is a university art museum in Johannesburg, South Africa, known for its extensive collection of African art and its role in research and education at the University of the Witwatersrand.
-
C.
WAMM
WAMM is the ICAO airport code for Sam Ratulangi International Airport serving Manado in North Sulawesi, Indonesia.
-
D.
WAMM
WAMM is the abbreviation for the World Association of the Major Metropolises, an international organization that brings together and represents the interests of the world’s largest cities.
-
E.
WAML
WAML is the ICAO airport code for Mutiara SIS Al-Jufrie Airport in Palu, Central Sulawesi, Indonesia.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b82fe88190a448597b7827f859 |
completed | April 17, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002da6e6e08190a20cc51699e12dbc |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.