Triple
T14421789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Android 5.0 Lollipop |
E357601
|
entity |
| Predicate | codename |
P2980
|
FINISHED |
| Object |
Lollipop
Lollipop is the codename for version 5.0 of the Android mobile operating system, known for introducing the Material Design interface and significant performance improvements.
|
E1099437
|
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: Lollipop | Statement: [Android 5.0 Lollipop, codename, Lollipop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lollipop Context triple: [Android 5.0 Lollipop, codename, Lollipop]
-
A.
Lollipop
"Lollipop" is a 2008 hit hip-hop single by Lil Wayne that became one of his most commercially successful and culturally influential songs.
-
B.
Lollipop
"Lollipop" is a catchy pop song by Mika, known for its playful lyrics and upbeat, cartoonish style.
-
C.
Lolly
Lolly is a diminutive or affectionate nickname commonly used for the given name Laura.
-
D.
Cotton Candy
"Cotton Candy" is a popular jazz album and title track by trumpeter Al Hirt, showcasing his bright, melodic style in the early 1960s.
-
E.
Lolly Lolly
"Lolly Lolly" is a funk-infused pop song by the duo Wendy & Lisa, known for its catchy groove and late-1980s production style.
- 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: Lollipop Triple: [Android 5.0 Lollipop, codename, Lollipop]
Generated description
Lollipop is the codename for version 5.0 of the Android mobile operating system, known for introducing the Material Design interface and significant performance improvements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lollipop Target entity description: Lollipop is the codename for version 5.0 of the Android mobile operating system, known for introducing the Material Design interface and significant performance improvements.
-
A.
Lollipop
"Lollipop" is a 2008 hit hip-hop single by Lil Wayne that became one of his most commercially successful and culturally influential songs.
-
B.
Lollipop
"Lollipop" is a catchy pop song by Mika, known for its playful lyrics and upbeat, cartoonish style.
-
C.
Lolly
Lolly is a diminutive or affectionate nickname commonly used for the given name Laura.
-
D.
Cotton Candy
"Cotton Candy" is a popular jazz album and title track by trumpeter Al Hirt, showcasing his bright, melodic style in the early 1960s.
-
E.
Lolly Lolly
"Lolly Lolly" is a funk-infused pop song by the duo Wendy & Lisa, known for its catchy groove and late-1980s production style.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91102c3c81908f571a1fff3bdd47 |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcb131c8190935d9bacb1afc995 |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5e188a148190bb166b7d50ad3b46 |
completed | May 8, 2026, 3:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5ea592cc8190a47a2f6a511c0549 |
completed | May 8, 2026, 3:55 a.m. |
Created at: April 10, 2026, 1:18 a.m.