Triple
T16047001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Lemon |
E389247
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Lemon |
E808192
|
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: Lemon | Statement: [Elizabeth Lemon, hasNickname, Lemon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lemon Context triple: [Elizabeth Lemon, hasNickname, Lemon]
-
A.
Lemon
Lemon is a 1993 song by U2 from their album "Zooropa," noted for its dance-oriented sound and Bono’s distinctive falsetto vocals.
-
B.
Lemon
chosen
Lemon is a citrus fruit known for its bright yellow color, sour taste, and wide use in cooking, beverages, and cleaning.
-
C.
Lemon
"Lemon" is a 2017 funk-infused hip hop single by N.E.R.D featuring Rihanna, known for its minimalist beat and distinctive rap-sung performance.
-
D.
Zitrone
Zitrone is a French surname most notably borne by Léon Zitrone, a prominent 20th-century television journalist and presenter in France.
-
E.
Grapefruit
Grapefruit is Yoko Ono’s influential 1964 conceptual art book of event scores and instructions that helped shape the development of Fluxus and conceptual art.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1835eda348190aff492f0ff668cce |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe476d4488190abade3d6b4011435 |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:56 a.m.