Triple
T4719247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Menken |
E104723
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Helen Menken |
E104723
|
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: Helen Menken | Statement: [Helen Menken, name, Helen Menken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Menken Context triple: [Helen Menken, name, Helen Menken]
-
A.
Helen Menken
chosen
Helen Menken was an American stage actress prominent in early 20th-century Broadway theatre and an influential figure in the New York theatrical community.
-
B.
Helen Gardner
Helen Gardner is a noted literary scholar and critic, best known for her influential work on English poetry and Renaissance literature.
-
C.
Helen Deutsch
Helen Deutsch was an American screenwriter best known for her work on classic mid-20th-century Hollywood films.
-
D.
Ellen Zinsser McCloy
Ellen Zinsser McCloy was the wife of influential American lawyer and statesman John J. McCloy, who played major roles in U.S. and international policy in the mid-20th century.
-
E.
Sally Kornbluth
Sally Kornbluth is an American cell biologist and academic leader who became the 18th president of the Massachusetts Institute of Technology.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd642779a08190b01e588d515cf498 |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be108bc0048190aeea8674f75105e5 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:18 p.m.