Triple
T9970480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jen Lindley |
E196189
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Jen |
E271644
|
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: Jen | Statement: [Jen Lindley, nickname, Jen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jen Context triple: [Jen Lindley, nickname, Jen]
-
A.
Jen
chosen
Jen is a common shortened form of the given name Jennifer, often used as a familiar or informal nickname.
-
B.
Jeni
Jeni is a common shortened form or nickname for the given name Jennifer.
-
C.
Jenny
Jenny is a caring and protective regal blue tang fish who is Dory’s mother in the animated film "Finding Dory."
-
D.
Jenny
Jenny is a central character in Kurt Weill and Bertolt Brecht’s opera "Rise and Fall of the City of Mahagonny," often portrayed as a pragmatic, disillusioned prostitute who embodies the work’s critique of capitalist excess and moral decay.
-
E.
Jenny
"Jenny" is a narrative poem by Dante Gabriel Rossetti that explores themes of desire, morality, and Victorian attitudes toward prostitution through a reflective monologue addressed to a fallen woman.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b7ea9881908a56f11e2e446dd0 |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23dca14d081909573e91a576921c9 |
completed | April 5, 2026, 10:47 a.m. |
Created at: March 30, 2026, 8:48 p.m.