Triple
T28315185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the second Mrs. de Winter |
E717113
|
entity |
| Predicate | relationshipToRebecca |
P201401
|
FINISHED |
| Object | successor as Maxim de Winter’s wife |
—
|
LITERAL 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: successor as Maxim de Winter’s wife | Statement: [the second Mrs. de Winter, relationshipToRebecca, successor as Maxim de Winter’s wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRebecca Context triple: [the second Mrs. de Winter, relationshipToRebecca, successor as Maxim de Winter’s wife]
-
A.
relationshipToBeth
Indicates the specific type of relationship or connection that an entity has to Beth.
-
B.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
C.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
D.
relationshipToMary
Indicates that one entity stands in a specified personal or social relationship to Mary.
-
E.
relationshipToVanessa
Indicates the specific type of personal or social relationship that an entity has with Vanessa.
- F. None of above. chosen
Provenance (4 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fff327d7788190a41ea5cbae060177 |
completed | May 10, 2026, 2:53 a.m. |
Created at: April 28, 2026, 12:19 a.m.