Triple
T13512134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy Darling |
E322665
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Darling |
E927610
|
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: Darling | Statement: [Wendy Darling, familyName, Darling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darling Context triple: [Wendy Darling, familyName, Darling]
-
A.
Darling
Darling is a 1965 British drama film directed by John Schlesinger, known for its incisive portrayal of a young woman's rise in London's high society and for winning multiple Academy Awards.
-
B.
Darling
Darling is a residential suburb in Melbourne, Victoria, known for its local train station on the Glen Waverley railway line and its proximity to the city.
-
C.
Darling
chosen
Darling is a surname most prominently associated with Ron Darling, a former Major League Baseball pitcher and current television baseball analyst.
-
D.
Darling
Darling is the kind, affectionate human owner of Lady in Disney's animated film "Lady and the Tramp."
-
E.
Darling
Darling is a South African wine-producing district known for its cool coastal climate and quality white and red wines, particularly Sauvignon Blanc.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d91e35881909a7184be0ad70c14 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:44 p.m.