Triple
T18572378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raffles Institution |
E453901
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object |
Sim Ann
Sim Ann is a Singaporean politician who has served as a Member of Parliament and held various ministerial positions in the Singapore government.
|
E1331372
|
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: Sim Ann | Statement: [Raffles Institution, hasAlumnus, Sim Ann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sim Ann Context triple: [Raffles Institution, hasAlumnus, Sim Ann]
-
A.
Shanghai Lil
"Shanghai Lil" is a musical number from the 1933 Warner Bros. film *Footlight Parade*, featuring James Cagney in a memorable song-and-dance performance.
-
B.
Lulu
Lulu is a fictional character best known from the Japanese film "Swallowtail Butterfly," in which she is portrayed by actress Ayumi Ito.
-
C.
Lulu
Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
-
D.
Lulu
Lulu is a Scottish singer and actress best known for her powerful pop vocals and hits like "To Sir with Love" and "Shout."
-
E.
Lulu
Lulu is a central character in the 1999 British cult film "Human Traffic," which explores the lives and clubbing culture of young people in Cardiff.
- 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: Sim Ann Triple: [Raffles Institution, hasAlumnus, Sim Ann]
Generated description
Sim Ann is a Singaporean politician who has served as a Member of Parliament and held various ministerial positions in the Singapore government.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sim Ann Target entity description: Sim Ann is a Singaporean politician who has served as a Member of Parliament and held various ministerial positions in the Singapore government.
-
A.
Shanghai Lil
"Shanghai Lil" is a musical number from the 1933 Warner Bros. film *Footlight Parade*, featuring James Cagney in a memorable song-and-dance performance.
-
B.
Lulu
Lulu is a fictional character best known from the Japanese film "Swallowtail Butterfly," in which she is portrayed by actress Ayumi Ito.
-
C.
Lulu
Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
-
D.
Lulu
Lulu is a central character in the 1999 British cult film "Human Traffic," which explores the lives and clubbing culture of young people in Cardiff.
-
E.
Lulu
Lulu is a Scottish singer and actress best known for her powerful pop vocals and hits like "To Sir with Love" and "Shout."
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b032488819098de683bb5c42c4b |
completed | April 19, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a04f886f2e88190bf01061cb793c0ab |
completed | May 13, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_6a04f9511eb08190952be765862cd1ab |
completed | May 13, 2026, 10:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04f9dd338881908b300bab7947f736 |
completed | May 13, 2026, 10:23 p.m. |
Created at: April 10, 2026, 11:43 a.m.