Triple
T4923201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Olympic Committee of Slovenia |
E110513
|
entity |
| Predicate | IOCCode |
P6277
|
FINISHED |
| Object |
SLO
SLO is the three-letter International Olympic Committee country code representing Slovenia in Olympic competitions.
|
E480078
|
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: SLO | Statement: [National Olympic Committee of Slovenia, IOCCode, SLO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SLO Context triple: [National Olympic Committee of Slovenia, IOCCode, SLO]
-
A.
Slocene
Slocene is a river in Latvia that serves as one of the tributaries feeding into the larger Lielupe River system.
-
B.
San Jo
San Jo is an informal nickname commonly used to refer to the city of San Jose, California.
-
C.
Ojai
Ojai is a small, scenic city in Southern California known for its arts community, boutique tourism, and surrounding mountains and orange groves.
-
D.
San Luis Obispo
San Luis Obispo is a small coastal city in California known for its historic downtown, nearby beaches and wineries, and its location along the scenic Highway 1 between Los Angeles and San Francisco.
-
E.
San
The San are an indigenous hunter-gatherer people of Southern Africa, known for their ancient rock art, click-based languages, and deep ecological knowledge of the Kalahari region.
- 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: SLO Triple: [National Olympic Committee of Slovenia, IOCCode, SLO]
Generated description
SLO is the three-letter International Olympic Committee country code representing Slovenia in Olympic competitions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SLO Target entity description: SLO is the three-letter International Olympic Committee country code representing Slovenia in Olympic competitions.
-
A.
Slocene
Slocene is a river in Latvia that serves as one of the tributaries feeding into the larger Lielupe River system.
-
B.
San Jo
San Jo is an informal nickname commonly used to refer to the city of San Jose, California.
-
C.
Ojai
Ojai is a small, scenic city in Southern California known for its arts community, boutique tourism, and surrounding mountains and orange groves.
-
D.
San Luis Obispo
San Luis Obispo is a small coastal city in California known for its historic downtown, nearby beaches and wineries, and its location along the scenic Highway 1 between Los Angeles and San Francisco.
-
E.
San
The San are an indigenous hunter-gatherer people of Southern Africa, known for their ancient rock art, click-based languages, and deep ecological knowledge of the Kalahari region.
- 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffd46748190843fed99f02fd8d5 |
completed | March 20, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77a6e1648190921487e3d81441b3 |
completed | March 21, 2026, 10:49 a.m. |
| NEDg | Description generation | batch_69be78292a988190ba51886095629b9c |
completed | March 21, 2026, 10:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be7892b34c819095100b14a80d6fa4 |
completed | March 21, 2026, 10:53 a.m. |
Created at: March 20, 2026, 1:30 p.m.