Triple
T23277029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenny Robertson |
E588749
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Ellen |
E62337
|
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: Ellen | Statement: [Jenny Robertson, notableWork, Ellen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellen Context triple: [Jenny Robertson, notableWork, Ellen]
-
A.
Ellen
chosen
"Ellen" is an American television sitcom starring Ellen DeGeneres that became especially notable for its groundbreaking coming-out episode in the 1990s.
-
B.
Ellen
Ellen is a feminine given name of Greek origin, commonly associated with meanings related to light or brightness.
-
C.
Ellen
Ellen is a central character in Kenneth Lonergan’s play "The Waverly Gallery," navigating the emotional and familial challenges surrounding her grandmother’s decline.
-
D.
Ellen
Ellen is a fictional character in Ken Follett's World War II-era thriller novel "Night Over Water."
-
E.
Ellen
Ellen is one of the central human survivors in Harlan Ellison’s dystopian science fiction story "I Have No Mouth, and I Must Scream," known for her complex psychological trauma and moral resilience under the torment of the supercomputer AM.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19578adf48190bdb129a55f86172c |
completed | April 29, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f7d1df88190bb71f663d677787f |
completed | May 19, 2026, 10:46 a.m. |
Created at: April 17, 2026, 4:48 p.m.