Triple
T8519608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Parsons |
E201663
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Lucy
Lucy is a common feminine given name of Latin origin meaning "light," widely used in English-speaking countries and beyond.
|
E413348
|
NE FINISHED |
How this triple was built (4 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: [Lucy Parsons, givenName, Lucy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Context triple: [Lucy Parsons, givenName, Lucy]
-
A.
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.
-
B.
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.
-
C.
Lucy
Lucy is the given name of Lucy Flucker Knox, the wife of American Revolutionary War General Henry Knox and a notable figure in early American history.
-
D.
Lucy
Lucy, better known by her nickname Wyldstyle, is a rebellious and resourceful Master Builder from The Lego Movie franchise.
-
E.
Lucy
Lucy is a fictional lion character, likely depicted with anthropomorphic traits in a narrative or animated context.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lucy Triple: [Lucy Parsons, givenName, Lucy]
Generated description
Lucy is a common feminine given name of Latin origin meaning "light," widely used in English-speaking countries and beyond.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lucy Target entity description: Lucy is a common feminine given name of Latin origin meaning "light," widely used in English-speaking countries and beyond.
-
A.
Lucy
chosen
Lucy is a feminine given name of Latin origin meaning "light," commonly used in many English-speaking and European countries.
-
B.
Lucy
Lucy is the given name of Lucy Flucker Knox, the wife of American Revolutionary War General Henry Knox and a notable figure in early American history.
-
C.
Lucy
Lucy, better known by her nickname Wyldstyle, is a rebellious and resourceful Master Builder from The Lego Movie franchise.
-
D.
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.
-
E.
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.
- F. None of above.
Provenance (5 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe627de908190b463da0f26da4ffb |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d37df3081909d8d38363b8d2304 |
completed | April 2, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_69ce6e69213c8190add7eb9cc74b1a33 |
completed | April 2, 2026, 1:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce6f28ae6481909a8a13613f3eb5e0 |
completed | April 2, 2026, 1:29 p.m. |
Created at: March 30, 2026, 6:16 p.m.