Triple
T20479793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney Institute for Astronomy |
E502420
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
SIfA
SIfA is the Sydney Institute for Astronomy, a research and teaching center at the University of Sydney focused on astronomical and astrophysical studies.
|
E1432950
|
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: SIfA | Statement: [Sydney Institute for Astronomy, shortName, SIfA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIfA Context triple: [Sydney Institute for Astronomy, shortName, SIfA]
-
A.
SIF
SIF is the commonly used abbreviation for the Italian Physical Society, a national organization dedicated to the advancement and promotion of physics in Italy.
-
B.
SIF
SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
-
C.
SIF
SIF is the Swiss federal body responsible for shaping and coordinating Switzerland’s international financial, tax, and monetary policy.
-
D.
SIF
SIF is a Canadian federal funding program that supports large-scale, transformative business and innovation projects to drive economic growth and competitiveness.
-
E.
Si
Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
- 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: SIfA Triple: [Sydney Institute for Astronomy, shortName, SIfA]
Generated description
SIfA is the Sydney Institute for Astronomy, a research and teaching center at the University of Sydney focused on astronomical and astrophysical studies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SIfA Target entity description: SIfA is the Sydney Institute for Astronomy, a research and teaching center at the University of Sydney focused on astronomical and astrophysical studies.
-
A.
SIF
SIF is the commonly used abbreviation for the Italian Physical Society, a national organization dedicated to the advancement and promotion of physics in Italy.
-
B.
SIF
SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
-
C.
SIF
SIF is the Swiss federal body responsible for shaping and coordinating Switzerland’s international financial, tax, and monetary policy.
-
D.
SIF
SIF is a Canadian federal funding program that supports large-scale, transformative business and innovation projects to drive economic growth and competitiveness.
-
E.
Si
Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b55d7a881909dfe3ea0e74b742b |
completed | April 20, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a088b25667081909e92bb990b7b4856 |
completed | May 16, 2026, 3:20 p.m. |
| NEDg | Description generation | batch_6a088c58f6748190b9945d6bff0f4b8c |
completed | May 16, 2026, 3:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a088cdecf04819097d6e934acc6c70f |
completed | May 16, 2026, 3:27 p.m. |
Created at: April 16, 2026, 11:34 a.m.