Triple
T13762827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lili Jellinek |
E330656
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lili |
E825867
|
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: Lili | Statement: [Lili Jellinek, givenName, Lili]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lili Context triple: [Lili Jellinek, givenName, Lili]
-
A.
Lili
Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
-
B.
Lili
Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
-
C.
Lilli
chosen
Lilli is a feminine given name, often used in German-speaking and other European countries, and famously borne by the actress Lilli Palmer.
-
D.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
E.
Lila
Lila is a character from the Peanuts universe who appears in the animated film "Snoopy, Come Home" as Snoopy’s original owner.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02250f4881908d5193b3d5d25844 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06faed88190abc44e6256cb9301 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:10 p.m.