Triple
T1536989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkansas |
E32572
|
entity |
| Predicate | postalAbbreviation |
P43
|
FINISHED |
| Object |
AR
AR is the official two-letter United States Postal Service abbreviation for the state of Arkansas.
|
E176545
|
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: AR | Statement: [Arkansas, postalAbbreviation, AR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AR Context triple: [Arkansas, postalAbbreviation, AR]
-
A.
AR
AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
-
B.
AR
AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
-
C.
AR
AR is the two-letter IATA airline designator assigned to Aerolíneas Argentinas, the flag carrier of Argentina.
-
D.
ARS
ARS is the principal in-house research agency of the United States Department of Agriculture, conducting scientific studies to improve agriculture, food safety, and environmental quality.
-
E.
ARC
ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
- 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: AR Triple: [Arkansas, postalAbbreviation, AR]
Generated description
AR is the official two-letter United States Postal Service abbreviation for the state of Arkansas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AR Target entity description: AR is the official two-letter United States Postal Service abbreviation for the state of Arkansas.
-
A.
AR
AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
-
B.
AR
AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
-
C.
AR
AR is the two-letter IATA airline designator assigned to Aerolíneas Argentinas, the flag carrier of Argentina.
-
D.
ARS
ARS is the principal in-house research agency of the United States Department of Agriculture, conducting scientific studies to improve agriculture, food safety, and environmental quality.
-
E.
ARC
ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90829e60081909d3f9f79585e080e |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad309714c4819090b995198d497ea2 |
completed | March 8, 2026, 8:17 a.m. |
| NEDg | Description generation | batch_69ad31167b748190bbb73d7369570ada |
completed | March 8, 2026, 8:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad31b5ce308190ba34123a4c8b8188 |
completed | March 8, 2026, 8:22 a.m. |
Created at: March 4, 2026, 7:26 p.m.