Triple
T9970063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy and Lucy |
E196180
|
entity |
| Predicate | hasAnimalCharacter |
P25502
|
FINISHED |
| Object | Lucy |
E323600
|
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: Lucy | Statement: [Wendy and Lucy, hasAnimalCharacter, Lucy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Context triple: [Wendy and Lucy, hasAnimalCharacter, Lucy]
-
A.
Lucy
chosen
Lucy is a fictional lion character, likely depicted with anthropomorphic traits in a narrative or animated context.
-
B.
Lucy
Lucy is a feminine given name of Latin origin meaning "light," commonly used in many English-speaking and European countries.
-
C.
Lucy
"Lucy" is a 2014 science fiction action film directed by Luc Besson, in which Scarlett Johansson plays a woman who gains extraordinary mental and physical abilities after a drug enters her system.
-
D.
Lucy
Lucy Hawking is a British journalist, novelist, and educator best known for her children’s science books co-written with her father, physicist Stephen Hawking.
-
E.
Lucy
Lucy is a NASA Discovery Program space mission designed to study Jupiter’s Trojan asteroids to better understand the early solar system’s formation and evolution.
- 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.