Triple
T16333766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Baker |
E396621
|
entity |
| Predicate | writingPartner |
P49107
|
FINISHED |
| Object | Pip Baker |
E353333
|
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: Pip Baker | Statement: [Jane Baker, writingPartner, Pip Baker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pip Baker Context triple: [Jane Baker, writingPartner, Pip Baker]
-
A.
Pip Baker
chosen
Pip Baker was a British television writer best known for co-writing several 1980s Doctor Who serials with his wife Jane Baker.
-
B.
Pip Karmel
Pip Karmel is an Australian film editor and director best known for her acclaimed editing work on the film "Shine."
-
C.
Pip Torrens
Pip Torrens is a British actor known for his character roles in film and television, including appearances in series such as "Patrick Melrose," "The Crown," and "Preacher."
-
D.
Noël Piper
Noël Piper is an American Christian author and speaker known for her writings on faith, family, and hospitality, and for her long-time ministry partnership with her husband, theologian John Piper.
-
E.
Peigi Barker
Peigi Barker is a Scottish child voice actress best known for portraying young Merida in Disney Pixar's animated film "Brave."
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e1da1081909bec6e77e6109dce |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dabc89481908005f5b2060abded |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.