Triple
T10466660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alphabetical Order |
E246813
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Lucy |
E413348
|
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: [Alphabetical Order, hasCharacter, Lucy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Context triple: [Alphabetical Order, hasCharacter, Lucy]
-
A.
Lucy
Lucy is a fictional lion character, likely depicted with anthropomorphic traits in a narrative or animated context.
-
B.
Lucy
chosen
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 NASA Discovery Program space mission designed to study Jupiter’s Trojan asteroids to better understand the early solar system’s formation and evolution.
-
D.
Lucy
Lucy is the dog companion in the independent drama film "Wendy and Lucy," symbolizing loyalty and hardship in the protagonist's journey.
-
E.
Lucy
Lucy is a character portrayed by English actress Ellise Chappell, known for her work in film and television.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092d6d408190b6bda4d7ced4601e |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc5c26a88190aab4a590c20191a3 |
completed | April 10, 2026, 11:17 a.m. |
Created at: April 6, 2026, 12:19 p.m.