Triple
T19295706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glen |
E482555
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Glenda |
—
|
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: Glenda | Statement: [Glen, relatedName, Glenda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glenda Context triple: [Glen, relatedName, Glenda]
-
A.
Glenda
chosen
Glenda is a character from the horror-comedy film "Seed of Chucky," known as the gender-fluid child of the killer dolls Chucky and Tiffany.
-
B.
Glenda
Glenda is a feminine given name most notably borne by acclaimed English actress and politician Glenda Jackson.
-
C.
Glen or Glenda
Glen or Glenda is a 1953 low-budget cult film by Ed Wood that explores cross-dressing and gender identity through a highly unconventional, semi-autobiographical narrative.
-
D.
Gladys
Gladys is a feminine given name of English origin that was especially popular in the late 19th and early 20th centuries.
-
E.
Glennis
Glennis is a feminine given name, best known for belonging to Glennis Dickhouse Yeager, the wife of test pilot Chuck Yeager and namesake of the Bell X-1 aircraft "Glamorous Glennis."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc8533c08190822a917ffa32812d |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.