Triple
T10028005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmen Dillon |
E204779
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Carmen Dillon |
E204779
|
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: Carmen Dillon | Statement: [Carmen Dillon, name, Carmen Dillon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmen Dillon Context triple: [Carmen Dillon, name, Carmen Dillon]
-
A.
Carmen Dillon
chosen
Carmen Dillon was an acclaimed British film art director and production designer, noted for her meticulous period detail and work on numerous classic mid-20th-century films.
-
B.
Carmen Mackenna
Carmen Mackenna was a 19th-century Chilean woman best known as the mother of prominent historian and politician Benjamín Vicuña Mackenna.
-
C.
Kate O'Toole
Kate O'Toole is a British actress known for her work in film, television, and theatre, and for being the daughter of acclaimed actor Peter O'Toole.
-
D.
Leonora O’Reilly
Leonora O’Reilly was an American labor organizer and suffragist who became a prominent figure in the early 20th-century women’s rights and labor movements.
-
E.
Dolores Malargie
Dolores Malargie was the mother of Argentine aviation pioneer and national figure Jorge Newbery.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde51c408190afb34010b1707014 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cb9a62788190aed75d03f1d2aeb6 |
completed | April 5, 2026, 8:52 p.m. |
Created at: March 30, 2026, 8:54 p.m.