Triple
T8389070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Cecilia Underwood |
E197893
|
entity |
| Predicate | honorificPrefix |
P536
|
FINISHED |
| Object | Lady |
E278084
|
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: Lady | Statement: [Lady Cecilia Underwood, honorificPrefix, Lady]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lady Context triple: [Lady Cecilia Underwood, honorificPrefix, Lady]
-
A.
Lady
"Lady" is a 1980 country-pop love ballad by Kenny Rogers, written and produced by Lionel Richie, that became one of Rogers' signature hits.
-
B.
Lady
chosen
Lady is a traditional British honorific title used for women of certain ranks within the nobility and aristocracy.
-
C.
Lady
Lady is the refined cocker spaniel protagonist from Disney’s animated film "Lady and the Tramp."
-
D.
Lady L
Lady L is a 1965 romantic comedy film, based on a Romain Gary novel, known for its satirical take on love and class in early 20th-century Europe and starring Sophia Loren, Paul Newman, and David Niven.
-
E.
Ladyzhyn
Ladyzhyn is a small industrial city in central Ukraine known for its power plant and location along the Southern Bug River.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81090f688190a3a8d1680383c361 |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce02cb3a1481908d30993d47c70039 |
completed | April 2, 2026, 5:46 a.m. |
Created at: March 30, 2026, 6:03 p.m.