Triple
T21899003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenny Schecter |
E540757
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object | Dana Fairbanks |
—
|
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: Dana Fairbanks | Statement: [Jenny Schecter, hasFriend, Dana Fairbanks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Fairbanks Context triple: [Jenny Schecter, hasFriend, Dana Fairbanks]
-
A.
Dana Fairbanks
chosen
Dana Fairbanks is a fictional professional tennis player and one of the central friends in the ensemble cast of the television drama series "The L Word."
-
B.
Dana Congdon
Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
-
C.
Emily Drinkard
Emily Drinkard, better known as Cissy Houston, is an American soul and gospel singer and the mother of Whitney Houston.
-
D.
Laura Bickford
Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
-
E.
Susan Blanchard
Susan Blanchard is an American socialite and former Broadway production assistant best known as the third wife of actor Henry Fonda.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc8c2108190b55ff1ba3badc9fb |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.