Triple
T14397215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lili Gentle |
E356979
|
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 Gentle, givenName, Lili]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lili Context triple: [Lili Gentle, 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 novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
-
E.
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.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90826f908190b3969af9b7cf922f |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551cbdb08190a9ea53e607f2555b |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.