Triple
T12038763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Dayle Hearn |
E286606
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | KHJ-TV |
E623332
|
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: KHJ-TV | Statement: [Francis Dayle Hearn, employer, KHJ-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KHJ-TV Context triple: [Francis Dayle Hearn, employer, KHJ-TV]
-
A.
KHJ (AM)
KHJ (AM) is a historic Los Angeles radio station best known for its influential "Boss Radio" Top 40 format in the 1960s and 1970s.
-
B.
KWHY-TV
chosen
KWHY-TV is a Spanish-language independent television station serving the Los Angeles, California market.
-
C.
KSAZ-TV
KSAZ-TV is a Fox-affiliated television station serving the Phoenix, Arizona market.
-
D.
KING-TV
KING-TV is a Seattle-based NBC-affiliated television station known for its local news coverage and for originating popular educational programs such as "Bill Nye the Science Guy."
-
E.
KSL-TV
KSL-TV is a television station based in Salt Lake City, Utah, known for its local news coverage and affiliation with the NBC network.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040a8be881908f4841145a7b4e86 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d9937a08190b2f606a1e55733b5 |
completed | May 1, 2026, 12:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.