Triple
T35221045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanne Siegel |
E1016953
|
entity |
| Predicate | wroteLettersTo |
P42917
|
FINISHED |
| Object | Warner Bros. |
—
|
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: Warner Bros. | Statement: [Joanne Siegel, wroteLettersTo, Warner Bros.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteLettersTo Context triple: [Joanne Siegel, wroteLettersTo, Warner Bros.]
-
A.
writesLettersTo
chosen
Indicates that one entity composes and sends letters directed to another entity.
-
B.
letters
Indicates that one entity is composed of, represented by, or associated with specific alphabetic characters or written symbols.
-
C.
letterWrittenFrom
Indicates that a letter is authored at or sent from a particular origin location or source entity.
-
D.
lettersWrittenBetween
Indicates that letters have been written and exchanged between the two entities, reflecting a mutual correspondence.
-
E.
correspondedWith
Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
- F. None of above.
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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.