Triple
T7503056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amur Khabarovsk |
E177312
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
AMR
AMR is the commonly used abbreviation for the Russian professional ice hockey club Amur Khabarovsk, which competes in the Kontinental Hockey League (KHL).
|
E668292
|
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: AMR | Statement: [Amur Khabarovsk, abbreviation, AMR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AMR Context triple: [Amur Khabarovsk, abbreviation, AMR]
-
A.
AMRO
AMRO is the World Health Organization’s Regional Office responsible for public health leadership and coordination across the Americas.
-
B.
AMR Corporation
AMR Corporation was a major American airline holding company best known as the former parent of American Airlines and its regional affiliates.
-
C.
AMF
AMF is a core 5G network function responsible for managing user access, registration, mobility, and connection handling between devices and the mobile network.
-
D.
AMF
AMF is a regional Arab financial institution that promotes monetary cooperation, economic integration, and development among its member states.
-
E.
AMM
AMM is the commonly used abbreviation for the APEC Ministerial Meeting, the annual gathering of Asia-Pacific Economic Cooperation foreign and trade ministers.
- 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: AMR Triple: [Amur Khabarovsk, abbreviation, AMR]
Generated description
AMR is the commonly used abbreviation for the Russian professional ice hockey club Amur Khabarovsk, which competes in the Kontinental Hockey League (KHL).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AMR Target entity description: AMR is the commonly used abbreviation for the Russian professional ice hockey club Amur Khabarovsk, which competes in the Kontinental Hockey League (KHL).
-
A.
AMRO
AMRO is the World Health Organization’s Regional Office responsible for public health leadership and coordination across the Americas.
-
B.
AMR Corporation
AMR Corporation was a major American airline holding company best known as the former parent of American Airlines and its regional affiliates.
-
C.
AMF
AMF is a core 5G network function responsible for managing user access, registration, mobility, and connection handling between devices and the mobile network.
-
D.
AMF
AMF is a regional Arab financial institution that promotes monetary cooperation, economic integration, and development among its member states.
-
E.
AMM
AMM is the commonly used abbreviation for the APEC Ministerial Meeting, the annual gathering of Asia-Pacific Economic Cooperation foreign and trade ministers.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b32c708190bb3a92d0d949304a |
completed | March 27, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c9953e88190a1e0e899f2ddf822 |
completed | March 28, 2026, 8:39 p.m. |
| NEDg | Description generation | batch_69c83defe434819086bf6d63c8f2675e |
completed | March 28, 2026, 8:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83e531ea881909b6186de9adbccc0 |
completed | March 28, 2026, 8:47 p.m. |
Created at: March 27, 2026, 3:44 p.m.