Triple
T4281428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheffield Steelers |
E97157
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
SHE
SHE is the standard abbreviation used for the Sheffield Steelers, a professional ice hockey team based in Sheffield, England.
|
E426232
|
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: SHE | Statement: [Sheffield Steelers, hasAbbreviation, SHE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SHE Context triple: [Sheffield Steelers, hasAbbreviation, SHE]
-
A.
She
"She" is a track by the American punk rock band Green Day from their breakthrough 1994 album *Dookie*.
-
B.
Her
"Her" is a lesser-known work by American poet, painter, and City Lights Books co-founder Lawrence Ferlinghetti, reflecting his characteristic Beat-influenced, avant-garde literary style.
-
C.
Her
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
-
D.
Her
"Her" is a soulful R&B song by American singer-songwriter SiR, known for its smooth production and introspective lyrics about love and vulnerability.
-
E.
HER
HER is the official herbarium code assigned to the Berggarten botanical collection, used in scientific and taxonomic references.
- 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: SHE Triple: [Sheffield Steelers, hasAbbreviation, SHE]
Generated description
SHE is the standard abbreviation used for the Sheffield Steelers, a professional ice hockey team based in Sheffield, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SHE Target entity description: SHE is the standard abbreviation used for the Sheffield Steelers, a professional ice hockey team based in Sheffield, England.
-
A.
She
"She" is a track by the American punk rock band Green Day from their breakthrough 1994 album *Dookie*.
-
B.
Her
"Her" is a lesser-known work by American poet, painter, and City Lights Books co-founder Lawrence Ferlinghetti, reflecting his characteristic Beat-influenced, avant-garde literary style.
-
C.
Her
"Her" is a soulful R&B song by American singer-songwriter SiR, known for its smooth production and introspective lyrics about love and vulnerability.
-
D.
Her
Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
-
E.
HER
HER is the commonly used abbreviation for the Harvard Educational Review, a scholarly journal focused on education research and policy.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503938f481909505e0a322dd2b6c |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7bb0168819082a49347fdfe0997 |
completed | March 14, 2026, 7:32 p.m. |
| NEDg | Description generation | batch_69b5b88fc3c08190acc376d3c3ccd147 |
completed | March 14, 2026, 7:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b8eada308190809db5c4ff7eeac6 |
completed | March 14, 2026, 7:37 p.m. |
Created at: March 12, 2026, 11:07 p.m.