Triple
T13799561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HV71 |
E331602
|
entity |
| Predicate | nickName |
P2937
|
FINISHED |
| Object |
HV
HV is the common nickname for HV71, a professional ice hockey club based in Jönköping, Sweden.
|
E1062017
|
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: HV | Statement: [HV71, nickName, HV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HV Context triple: [HV71, nickName, HV]
-
A.
HV
HV is the IATA airline designator used by Transavia, a Dutch low-cost carrier operating scheduled and charter flights across Europe and surrounding regions.
-
B.
HF
HF is the Faculty of Humanities at the University of Oslo, encompassing disciplines such as languages, history, culture, and philosophy.
-
C.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
D.
HY
HY is the vehicle registration code used on license plates for vehicles registered in the Finnish town of Hyvinkää.
-
E.
HY
HY is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
- 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: HV Triple: [HV71, nickName, HV]
Generated description
HV is the common nickname for HV71, a professional ice hockey club based in Jönköping, Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HV Target entity description: HV is the common nickname for HV71, a professional ice hockey club based in Jönköping, Sweden.
-
A.
HV
HV is the IATA airline designator used by Transavia, a Dutch low-cost carrier operating scheduled and charter flights across Europe and surrounding regions.
-
B.
HF
HF is the Faculty of Humanities at the University of Oslo, encompassing disciplines such as languages, history, culture, and philosophy.
-
C.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
D.
HY
HY is the vehicle registration code used on license plates for vehicles registered in the Finnish town of Hyvinkää.
-
E.
HY
HY is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69f7b138fda88190b2b7ffb51ce02a40 |
completed | May 3, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b28ca218819097fc35042d3b278a |
completed | May 3, 2026, 8:39 p.m. |
Created at: April 9, 2026, 10:11 p.m.