Triple
T11210710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota Motor Manufacturing Kentucky |
E265296
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
TMMK
TMMK is Toyota’s large-scale automobile manufacturing plant in Georgetown, Kentucky, known for producing popular Toyota and Lexus models for the North American market.
|
E911980
|
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: TMMK | Statement: [Toyota Motor Manufacturing Kentucky, abbreviation, TMMK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TMMK Context triple: [Toyota Motor Manufacturing Kentucky, abbreviation, TMMK]
-
A.
TMM
TMM was the former currency code for the original Turkmenistan manat used before the country's monetary redenomination.
-
B.
MMK
MMK is the three-letter ISO 4217 currency code for the Myanmar kyat, the official currency of Myanmar.
-
C.
TKM
TKM is the three-letter ISO 3166-1 alpha-3 country code assigned to Turkmenistan.
-
D.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
-
E.
MMK 3
MMK 3 is a satellite venue of Frankfurt’s Museum für Moderne Kunst that hosts contemporary art exhibitions and projects in an off-site, experimental setting.
- 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: TMMK Triple: [Toyota Motor Manufacturing Kentucky, abbreviation, TMMK]
Generated description
TMMK is Toyota’s large-scale automobile manufacturing plant in Georgetown, Kentucky, known for producing popular Toyota and Lexus models for the North American market.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TMMK Target entity description: TMMK is Toyota’s large-scale automobile manufacturing plant in Georgetown, Kentucky, known for producing popular Toyota and Lexus models for the North American market.
-
A.
TMM
TMM was the former currency code for the original Turkmenistan manat used before the country's monetary redenomination.
-
B.
MMK
MMK is the three-letter ISO 4217 currency code for the Myanmar kyat, the official currency of Myanmar.
-
C.
TKM
TKM is the three-letter ISO 3166-1 alpha-3 country code assigned to Turkmenistan.
-
D.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
-
E.
MMK 3
MMK 3 is a satellite venue of Frankfurt’s Museum für Moderne Kunst that hosts contemporary art exhibitions and projects in an off-site, experimental setting.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d6f5d4819086dcb776a0d469e8 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e49747ec288190bc3e826b6de7f6f2 |
completed | April 19, 2026, 8:50 a.m. |
| NEDg | Description generation | batch_69e49c0a92b08190ac5debb7d67ca776 |
completed | April 19, 2026, 9:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e49e8dc4ec81908d0defe77827d197 |
completed | April 19, 2026, 9:21 a.m. |
Created at: April 8, 2026, 9:30 p.m.