Triple
T4407109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Eleanor Dall |
E93760
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Eleanor |
E5505
|
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: Eleanor | Statement: [Anna Eleanor Dall, middleName, Eleanor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eleanor Context triple: [Anna Eleanor Dall, middleName, Eleanor]
-
A.
Eleanor
chosen
Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
-
B.
Eleanor
Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
-
C.
Katherine
Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
-
D.
Isabella
Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
-
E.
Isabella
Isabella was a 15th-century Aragonese princess who became Queen of Portugal through her marriage to King Manuel I.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548b1ca08190b3136867c7098d86 |
completed | March 13, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f609f7f881909d12735f4028a108 |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:28 p.m.