Triple
T7530254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knots Landing |
E178002
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Michelle Phillips |
E238642
|
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: Michelle Phillips | Statement: [Knots Landing, starring, Michelle Phillips]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Phillips Context triple: [Knots Landing, starring, Michelle Phillips]
-
A.
Michelle Phillips
chosen
Michelle Phillips is an American singer, songwriter, and actress best known as a member of the 1960s folk-rock group The Mamas & the Papas.
-
B.
Nancy Wilson
Nancy Wilson was an acclaimed American jazz and pop vocalist known for her sophisticated phrasing, emotional depth, and a career spanning over five decades.
-
C.
Nancy Wilson
Nancy Wilson is an American musician and composer best known as the guitarist and co-founder of the rock band Heart and for her work scoring films.
-
D.
Stacy Lattisaw
Stacy Lattisaw is an American R&B singer best known for her successful run of soulful hits in the late 1970s and 1980s, including the song "Let Me Be Your Angel."
-
E.
Susan Hendricks
Susan Hendricks is an American television journalist and news anchor best known for her work with CNN and HLN.
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81fbd4c8190b8ffedf1dbbb43aa |
completed | March 27, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8463e08ac8190abd4d19b58067233 |
completed | March 28, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:47 p.m.