Triple
T15996438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Mark Greene |
E387977
|
entity |
| Predicate | colleague |
P398
|
FINISHED |
| Object | Dr. Kerry Weaver |
E387023
|
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: Dr. Kerry Weaver | Statement: [Dr. Mark Greene, colleague, Dr. Kerry Weaver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dr. Kerry Weaver Context triple: [Dr. Mark Greene, colleague, Dr. Kerry Weaver]
-
A.
Dr. Kerry Weaver
chosen
Dr. Kerry Weaver is a prominent, complex physician and administrator on the medical drama series "ER," known for her authoritative leadership style, personal struggles, and evolving relationships with colleagues.
-
B.
Mona McHenry
Mona McHenry was the wife of Canadian actor John Colicos, known for his work in film, television, and theater.
-
C.
Stacey Waite
Stacey Waite is an American poet, educator, and scholar known for work exploring gender, queerness, and pedagogy.
-
D.
Melissa Franklin
Melissa Franklin is a Canadian-American experimental particle physicist known for her work at CERN and as the first woman to receive tenure in Harvard University's physics department.
-
E.
Rachel Roberts
Rachel Roberts is a Canadian model and actress known for her work in fashion campaigns and films such as "Simone" and "Entourage."
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157882ef0819081143e530bd6413c |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbca65a4819090109589dba7f7a9 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:55 a.m.