Triple
T22321015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Hannigan |
E551783
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Marta Kauffman |
—
|
NE NERFINISHED |
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: Marta Kauffman | Statement: [Mike Hannigan, creator, Marta Kauffman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marta Kauffman Context triple: [Mike Hannigan, creator, Marta Kauffman]
-
A.
Marta Kauffman
chosen
Marta Kauffman is an American television writer and producer best known as the co-creator of the hit sitcom "Friends."
-
B.
Stacey Sher
Stacey Sher is an American film and television producer known for her work on acclaimed movies such as "Django Unchained," "Pulp Fiction," and "Erin Brockovich."
-
C.
Gillian Sankoff
Gillian Sankoff is a sociolinguist renowned for her pioneering work on language variation and change, particularly in French and in multilingual communities such as Papua New Guinea.
-
D.
Suzanne Balk
Suzanne Balk is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
-
E.
Alison Leslie Gold
Alison Leslie Gold is an American author best known for her works on Holocaust history and memory, including collaborations related to Anne Frank.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15764d3a48190af79ce4642b7f563 |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:42 p.m.