Triple
T22475211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australopithecus afarensis |
E555611
|
entity |
| Predicate | notableSpecimen |
P34841
|
FINISHED |
| Object |
Lucy
Lucy is a famous 3.2-million-year-old Australopithecus afarensis fossil whose discovery greatly advanced understanding of early human evolution.
|
E1538619
|
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: [Australopithecus afarensis, notableSpecimen, Lucy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Context triple: [Australopithecus afarensis, notableSpecimen, Lucy]
-
A.
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.
-
B.
Lucy
"Lucy" is a coming-of-age novella by Jamaica Kincaid that follows a young Caribbean woman navigating identity, colonial legacy, and independence while working as an au pair in the United States.
-
C.
Lucy
Lucy is a fictional character named in the context of "Loosies," likely serving as a supporting figure in that film’s narrative.
-
D.
Lucy
Lucy is a singer-songwriter and musician best known as a solo indie rock artist and as a member of the supergroup boygenius.
-
E.
Lucy
Lucy is the protagonist of the romance story "Kissing Lessons," around whom the central emotional and narrative developments revolve.
- 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: [Australopithecus afarensis, notableSpecimen, Lucy]
Generated description
Lucy is a famous 3.2-million-year-old Australopithecus afarensis fossil whose discovery greatly advanced understanding of early human evolution.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lucy Target entity description: Lucy is a famous 3.2-million-year-old Australopithecus afarensis fossil whose discovery greatly advanced understanding of early human evolution.
-
A.
Lucy
Lucy is a character portrayed by actress and filmmaker Alice Englert.
-
B.
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.
-
C.
Lucy
Lucy is a feminine given name of Latin origin meaning "light," commonly used in many English-speaking and European countries.
-
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 character in the medieval German legend of Venusberg, associated with the enchanted mountain realm of the goddess Venus.
- F. None of above. chosen
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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be3930c8190ba967196df7e083f |
completed | April 29, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b125dda888190a266454969014eb7 |
completed | May 18, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_6a0b1388d8a481908d61f578fde9991d |
completed | May 18, 2026, 1:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b1462413c819086c2de0e62b2648a |
completed | May 18, 2026, 1:30 p.m. |
Created at: April 16, 2026, 8:49 p.m.